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Session feel
\n
No streaks, shame, or productivity theatre. NeuroBait looks for the emotional anchor and turns it into a small action you can start now.
\n                ","html_template":"${value}","css_template":"","js_on_load":"element.addEventListener('click', function() { trigger('click') });","apply_default_css":true,"show_label":false,"visible":true,"elem_classes":[],"preserved_by_key":["value"],"container":false,"padding":false,"autoscroll":false,"buttons":[],"props":{},"name":"html","_selectable":false,"component_class_name":"HTML"},"skip_api":false,"component_class_id":"62e388cc5d1be0292a8c4de99a2c00282e7d8a4e020a96adc2ded85a8b315b8b","key":null,"api_info":{"type":"string"},"api_info_as_input":{"type":"string"},"api_info_as_output":{"type":"string"},"example_inputs":"
Hello
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1.0"},"example_inputs":0.2},{"id":15,"type":"slider","props":{"minimum":0.6,"maximum":1.0,"value":0.9,"step":0.05,"label":"Top p","show_label":true,"container":true,"min_width":160,"visible":true,"elem_classes":[],"preserved_by_key":["value"],"name":"slider","_selectable":false},"skip_api":false,"component_class_id":"0ac3736b4129faf84640f0058a8d346f4329c60284cd45c39454e44098df1b16","key":null,"api_info":{"type":"number","description":"numeric value between 0.6 and 1.0"},"api_info_as_input":{"type":"number","description":"numeric value between 0.6 and 1.0"},"api_info_as_output":{"type":"number","description":"numeric value between 0.6 and 1.0"},"example_inputs":0.6},{"id":16,"type":"form","props":{"scale":0,"min_width":0,"preserved_by_key":[],"name":"form"},"skip_api":true,"component_class_id":"ed5cd51f569f3a7624b1709c4e7e50a5a608037f5fb82307671a5cec77e36b71","key":null}],"css":"\n:root {\n  --nb-ink: #202624;\n  --nb-muted: #61706b;\n  --nb-paper: #faf7f0;\n  --nb-panel: #fffdf8;\n  --nb-line: #d8ded2;\n  --nb-sage: #6f8f7a;\n  --nb-clay: #b36a4c;\n  --nb-blue: #536d89;\n}\nbody, .gradio-container {\n  background: var(--nb-paper);\n  color: var(--nb-ink);\n  font-family: Inter, ui-sans-serif, system-ui, -apple-system, BlinkMacSystemFont, \"Segoe UI\", sans-serif;\n}\n.nb-shell {\n  max-width: 1120px;\n  margin: 0 auto;\n}\n.nb-title {\n  display: flex;\n  align-items: baseline;\n  justify-content: space-between;\n  gap: 16px;\n  padding: 18px 0 10px;\n  border-bottom: 1px solid var(--nb-line);\n}\n.nb-title h1 {\n  margin: 0;\n  font-size: 28px;\n  line-height: 1.1;\n  letter-spacing: 0;\n}\n.nb-title p {\n  margin: 0;\n  color: var(--nb-muted);\n  font-size: 14px;\n}\n.nb-layout {\n  display: grid;\n  grid-template-columns: minmax(0, 1fr) 280px;\n  gap: 18px;\n  margin-top: 18px;\n}\n.nb-side {\n  border-left: 1px solid var(--nb-line);\n  padding-left: 18px;\n}\n.nb-side h2 {\n  font-size: 14px;\n  margin: 0 0 10px;\n}\n.nb-side p {\n  color: var(--nb-muted);\n  font-size: 13px;\n  line-height: 1.45;\n}\n.nb-chatbot {\n  min-height: 580px;\n  border: 1px solid var(--nb-line);\n  background: var(--nb-panel);\n}\n.nb-chatbot .message {\n  border-radius: 8px !important;\n}\n.nb-input textarea {\n  border-radius: 8px !important;\n}\n.nb-examples button {\n  border-radius: 8px !important;\n  min-height: 38px;\n  text-align: left;\n}\n.nb-controls {\n  gap: 10px;\n}\n.nb-controls .wrap {\n  border-radius: 8px !important;\n}\nbutton.primary {\n  background: var(--nb-sage) !important;\n  border-color: var(--nb-sage) !important;\n}\n@media (max-width: 860px) {\n  .nb-title {\n    display: block;\n  }\n  .nb-title p {\n    margin-top: 8px;\n  }\n  .nb-layout {\n    grid-template-columns: 1fr;\n  }\n  .nb-side {\n    border-left: 0;\n    border-top: 1px solid var(--nb-line);\n    padding-left: 0;\n    padding-top: 14px;\n  }\n}\n","connect_heartbeat":false,"js":null,"head":null,"title":"Gradio","space_id":"build-small-hackathon/NeuroBait","enable_queue":true,"show_error":false,"footer_links":["api","gradio","settings"],"is_colab":false,"max_file_size":null,"stylesheets":[],"theme":"soft","protocol":"sse_v3","body_css":{"body_background_fill":"#fafaf9","body_text_color":"#292524","body_background_fill_dark":"#0f0e0d","body_text_color_dark":"#f5f5f4"},"fill_height":false,"fill_width":false,"theme_hash":"82da660fc3d9b14bcf3915d89d56354c7e440aa092c7fe5357eb5bdbd7327d69","pwa":true,"pages":[["","Home",true]],"page":{"":{"layout":{"id":0,"children":[{"id":1,"children":[]},{"id":2,"children":[{"id":3,"children":[{"id":4},{"id":10,"children":[{"id":5}]},{"id":6,"children":[{"id":7},{"id":8}]},{"id":9}]},{"id":11,"children":[{"id":12,"children":[]},{"id":13,"children":[{"id":16,"children":[{"id":14},{"id":15}]}]}]}]}]},"components":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16],"dependencies":[0,1,2,3,4,5]}},"mcp_server":false,"i18n_translations":null,"dependencies":[{"id":0,"targets":[[9,"click"]],"inputs":[9],"outputs":[5],"backend_fn":true,"js":null,"queue":false,"api_name":"load_example","api_description":null,"scroll_to_output":false,"show_progress":"hidden","show_progress_on":null,"batch":false,"max_batch_size":4,"cancels":[],"types":{"generator":false,"cancel":false},"collects_event_data":false,"trigger_after":null,"trigger_only_on_success":false,"trigger_only_on_failure":false,"trigger_mode":"once","api_visibility":"undocumented","rendered_in":null,"render_id":null,"connection":"sse","time_limit":null,"stream_every":0.5,"event_specific_args":null,"component_prop_inputs":[],"js_implementation":null},{"id":1,"targets":[[7,"click"]],"inputs":[5,4],"outputs":[5,4],"backend_fn":true,"js":null,"queue":false,"api_name":"user_turn","api_description":null,"scroll_to_output":false,"show_progress":"full","show_progress_on":null,"batch":false,"max_batch_size":4,"cancels":[],"types":{"generator":false,"cancel":false},"collects_event_data":false,"trigger_after":null,"trigger_only_on_success":false,"trigger_only_on_failure":false,"trigger_mode":"once","api_visibility":"public","rendered_in":null,"render_id":null,"connection":"sse","time_limit":null,"stream_every":0.5,"event_specific_args":null,"component_prop_inputs":[],"js_implementation":null},{"id":2,"targets":[[null,"then"]],"inputs":[4,14,15],"outputs":[4],"backend_fn":true,"js":null,"queue":true,"api_name":"bot_turn","api_description":null,"scroll_to_output":false,"show_progress":"full","show_progress_on":null,"batch":false,"max_batch_size":4,"cancels":[],"types":{"generator":false,"cancel":false},"collects_event_data":false,"trigger_after":1,"trigger_only_on_success":false,"trigger_only_on_failure":false,"trigger_mode":"once","api_visibility":"public","rendered_in":null,"render_id":null,"connection":"sse","time_limit":null,"stream_every":0.5,"event_specific_args":null,"component_prop_inputs":[],"js_implementation":null},{"id":3,"targets":[[5,"submit"]],"inputs":[5,4],"outputs":[5,4],"backend_fn":true,"js":null,"queue":false,"api_name":"user_turn_1","api_description":null,"scroll_to_output":false,"show_progress":"full","show_progress_on":null,"batch":false,"max_batch_size":4,"cancels":[],"types":{"generator":false,"cancel":false},"collects_event_data":false,"trigger_after":null,"trigger_only_on_success":false,"trigger_only_on_failure":false,"trigger_mode":"once","api_visibility":"public","rendered_in":null,"render_id":null,"connection":"sse","time_limit":null,"stream_every":0.5,"event_specific_args":null,"component_prop_inputs":[],"js_implementation":null},{"id":4,"targets":[[null,"then"]],"inputs":[4,14,15],"outputs":[4],"backend_fn":true,"js":null,"queue":true,"api_name":"bot_turn_1","api_description":null,"scroll_to_output":false,"show_progress":"full","show_progress_on":null,"batch":false,"max_batch_size":4,"cancels":[],"types":{"generator":false,"cancel":false},"collects_event_data":false,"trigger_after":3,"trigger_only_on_success":false,"trigger_only_on_failure":false,"trigger_mode":"once","api_visibility":"public","rendered_in":null,"render_id":null,"connection":"sse","time_limit":null,"stream_every":0.5,"event_specific_args":null,"component_prop_inputs":[],"js_implementation":null},{"id":5,"targets":[[8,"click"]],"inputs":[],"outputs":[4],"backend_fn":true,"js":null,"queue":false,"api_name":"lambda","api_description":null,"scroll_to_output":false,"show_progress":"full","show_progress_on":null,"batch":false,"max_batch_size":4,"cancels":[],"types":{"generator":false,"cancel":false},"collects_event_data":false,"trigger_after":null,"trigger_only_on_success":false,"trigger_only_on_failure":false,"trigger_mode":"once","api_visibility":"public","rendered_in":null,"render_id":null,"connection":"sse","time_limit":null,"stream_every":0.5,"event_specific_args":null,"component_prop_inputs":[],"js_implementation":null}],"layout":{"id":0,"children":[{"id":1,"children":[]},{"id":2,"children":[{"id":3,"children":[{"id":4},{"id":10,"children":[{"id":5}]},{"id":6,"children":[{"id":7},{"id":8}]},{"id":9}]},{"id":11,"children":[{"id":12,"children":[]},{"id":13,"children":[{"id":16,"children":[{"id":14},{"id":15}]}]}]}]}]},"username":null,"root":"https://build-small-hackathon-neurobait.hf.space"}


Halaman Gradio sekarang reachable HTTP 200 dan Space `RUNNING`. Dari `/config`, Gradio 6 default Chatbot memakai format `messages`, jadi saya akan selaraskan `user_turn/bot_turn` kembali ke dict messages agar event API dan UI konsisten.


Input:
*** Begin Patch
*** Update File: deploy/app.py
@@
-    def user_turn(user_message: str, chat_history: list) -> tuple[str, list]:
+    def user_turn(user_message: str, chat_history: list) -> tuple[str, list]:
         if not user_message.strip():
             return "", chat_history
-        return "", chat_history + [(user_message.strip(), None)]
+        return "", chat_history + [{"role": "user", "content": user_message.strip()}]

     def bot_turn(chat_history: list, temperature_value: float, top_p_value: float) -> list:
-        user_message = chat_history[-1][0]
+        user_message = chat_history[-1]["content"]
         assistant_message = respond(user_message, chat_history[:-1], temperature_value, top_p_value)
-        chat_history[-1] = (user_message, assistant_message)
-        return chat_history
+        return chat_history + [{"role": "assistant", "content": assistant_message}]
*** End Patch


Success. Updated the following files:
M deploy/app.py

@@ -285,9 +285,8 @@
             return "", chat_history
-        return "", chat_history + [(user_message.strip(), None)]
+        return "", chat_history + [{"role": "user", "content": user_message.strip()}]

     def bot_turn(chat_history: list, temperature_value: float, top_p_value: float) -> list:
-        user_message = chat_history[-1][0]
+        user_message = chat_history[-1]["content"]
         assistant_message = respond(user_message, chat_history[:-1], temperature_value, top_p_value)
-        chat_history[-1] = (user_message, assistant_message)
-        return chat_history
+        return chat_history + [{"role": "assistant", "content": assistant_message}]


Output:
Exit code: 0
Wall time: 0.1 seconds
Output:
Success. Updated the following files:
M deploy/app.py


Saya re-push sync format Chatbot messages. Setelah RUNNING lagi, saya akan coba call API `bot_turn` langsung.


/media/haris-subrata/Work/llm/agent_analytics/venv/bin/python -m modal run train/modal_train.py --no-run-train --push-space --check-space

Allow re-uploading the final Chatbot message-format fix and checking runtime?


Output:
Chunk ID: cf1491
Wall time: 15.2067 seconds
Process exited with code 0
Original token count: 432
Output:
✓ Initialized. View run at
https://modal.com/apps/harisabektidsubrata/main/ap-wf4ZMLZ4j2evEiBdXehDSd
✓ Created objects.
├── 🔨 Created mount
│   /media/haris-subrata/Work/llm/NeuroBait-Build-Small-Model/train/modal_train.
│   py
├── 🔨 Created mount
│   /media/haris-subrata/Work/llm/NeuroBait-Build-Small-Model/deploy
├── 🔨 Created mount model-card/README.md
├── 🔨 Created mount train/train_core.py
├── 🔨 Created mount data/train.jsonl
├── 🔨 Created mount data/eval.jsonl
├── 🔨 Created function preflight.
├── 🔨 Created function train.
├── 🔨 Created function push_lora_to_hub.
├── 🔨 Created function push_space_to_hub.
├── 🔨 Created function set_space_hardware.
├── 🔨 Created function get_space_runtime.
├── 🔨 Created function get_space_logs.
└── 🔨 Created function merge_and_push.
space repo: build-small-hackathon/NeuroBait
space runtime: {
  "repo_id": "build-small-hackathon/NeuroBait",
  "stage": "RUNNING_BUILDING",
  "hardware": "zero-a10g",
  "requested_hardware": "zero-a10g",
  "sleep_time": 172800,
  "raw": {
    "stage": "RUNNING_BUILDING",
    "hardware": {
      "current": "zero-a10g",
      "requested": "zero-a10g"
    },
    "gcTimeout": 172800,
    "replicas": {
      "current": 1,
      "requested": 1
    },
    "devMode": false,
    "domains": [
      {
        "domain": "build-small-hackathon-neurobait.hf.space",
        "stage": "READY"
      }
    ],
    "sha": "021c767d1e367ab3330b9d0ccc838ab515326ad7"
  }
}
Stopping app - local entrypoint completed.
✓ App completed. View run at
https://modal.com/apps/harisabektidsubrata/main/ap-wf4ZMLZ4j2evEiBdXehDSd


Runtime sekarang `RUNNING_BUILDING`, artinya versi lama masih melayani saat build baru dipasang. Saya tunggu sampai SHA baru aktif.


Output:
Chunk ID: b65de1
Wall time: 30.0006 seconds
Process running with session ID 28323
Original token count: 0
Output:


Masih menunggu build final aktif.


Output:
Chunk ID: fd1071
Wall time: 10.6817 seconds
Process exited with code 0
Original token count: 0
Output:


Output:
Chunk ID: 6d21a9
Wall time: 0.2008 seconds
Process exited with code 0
Original token count: 300
Output:
{"_id":"6a26dd980eccd859eba85b85","id":"build-small-hackathon/NeuroBait","sdk":"gradio","likes":0,"tags":["gradio","region:us"],"private":false,"author":"build-small-hackathon","sha":"2bc1ce730da2f74ca89d9667fb4eefbec325b2f1","lastModified":"2026-06-08T15:31:50.000Z","cardData":{"title":"NeuroBait","colorFrom":"green","colorTo":"blue","sdk":"gradio","app_file":"app.py","pinned":false,"license":"apache-2.0","short_description":"ADHD-friendly task initiation with one tiny next move."},"subdomain":"build-small-hackathon-neurobait","gated":false,"disabled":false,"host":"https://build-small-hackathon-neurobait.hf.space","models":["build-small-hackathon/NeuroBait","unsloth/gemma-4-26B-A4B-it"],"runtime":{"stage":"RUNNING","hardware":{"current":"zero-a10g","requested":"zero-a10g"},"gcTimeout":172800,"replicas":{"current":1,"requested":1},"devMode":false,"domains":[{"domain":"build-small-hackathon-neurobait.hf.space","stage":"READY"}],"sha":"2bc1ce730da2f74ca89d9667fb4eefbec325b2f1","pySpacesVersion":"0.50.4"},"siblings":[{"rfilename":".gitattributes"},{"rfilename":"README.md"},{"rfilename":"app.py"},{"rfilename":"requirements.txt"}],"createdAt":"2026-06-08T15:19:52.000Z","usedStorage":0}


Final build sudah `RUNNING` pada ZeroGPU. Saya akan test API event `bot_turn` dengan prompt pendek; ini akan memicu model loading pertama kali, jadi bisa memakan waktu atau terkena queue.


curl -s -X POST https://build-small-hackathon-neurobait.hf.space/gradio_api/call/bot_turn -H 'Content-Type: application/json' -d '{"data":[[{"role":"user","content":"I need to finish a presentation tomorrow, but I keep avoiding the first slide."}],0.7,0.9]}'


Output:
Chunk ID: 249a96
Wall time: 1.0037 seconds
Process exited with code 0
Original token count: 12
Output:
{"event_id":"18976b8a03f041b0bbbe3bb061e66387"}


API menerima event dan memberi `event_id`, jadi Gradio event route aktif. Saya sekarang baca stream hasilnya; ini bagian yang memicu load base+adapter di ZeroGPU.


curl -s -N https://build-small-hackathon-neurobait.hf.space/gradio_api/call/bot_turn/18976b8a03f041b0bbbe3bb061e66387


Output:
Chunk ID: 20383c
Wall time: 0.9867 seconds
Process exited with code 0
Original token count: 9
Output:
event: error
data: {"error": null}


Event route aktif tapi inference pertama error tanpa detail di public stream. Saya cek runtime API untuk error message; biasanya Space runtime menyimpan traceback terbaru kalau crash.


Output:
Chunk ID: 9d0933
Wall time: 0.2019 seconds
Process exited with code 0
Original token count: 300
Output:
{"_id":"6a26dd980eccd859eba85b85","id":"build-small-hackathon/NeuroBait","sdk":"gradio","likes":0,"tags":["gradio","region:us"],"private":false,"author":"build-small-hackathon","sha":"2bc1ce730da2f74ca89d9667fb4eefbec325b2f1","lastModified":"2026-06-08T15:31:50.000Z","cardData":{"title":"NeuroBait","colorFrom":"green","colorTo":"blue","sdk":"gradio","app_file":"app.py","pinned":false,"license":"apache-2.0","short_description":"ADHD-friendly task initiation with one tiny next move."},"subdomain":"build-small-hackathon-neurobait","gated":false,"disabled":false,"host":"https://build-small-hackathon-neurobait.hf.space","models":["build-small-hackathon/NeuroBait","unsloth/gemma-4-26B-A4B-it"],"runtime":{"stage":"RUNNING","hardware":{"current":"zero-a10g","requested":"zero-a10g"},"gcTimeout":172800,"replicas":{"current":1,"requested":1},"devMode":false,"domains":[{"domain":"build-small-hackathon-neurobait.hf.space","stage":"READY"}],"sha":"2bc1ce730da2f74ca89d9667fb4eefbec325b2f1","pySpacesVersion":"0.50.4"},"siblings":[{"rfilename":".gitattributes"},{"rfilename":"README.md"},{"rfilename":"app.py"},{"rfilename":"requirements.txt"}],"createdAt":"2026-06-08T15:19:52.000Z","usedStorage":0}


Kemungkinan error-nya format pesan Gradio 6: `content` dari Chatbot bisa berupa list block text, bukan string. Saya akan buat normalizer konten yang support string maupun `[{type/text}]`, lalu nyalakan `show_error=True` untuk debugging publik sementara.


Input:
*** Begin Patch
*** Update File: deploy/app.py
@@
 def _content_blocks(messages: list[dict]) -> list[dict]:
@@
     return normalized

+def _message_text(content) -> str:
+    if isinstance(content, str):
+        return content.strip()
+    if isinstance(content, list):
+        parts = []
+        for item in content:
+            if isinstance(item, dict):
+                text = item.get("text")
+                if isinstance(text, str):
+                    parts.append(text)
+        return " ".join(part.strip() for part in parts if part.strip()).strip()
+    return ""
+
+
 def _load_model():
@@
         if isinstance(item, dict):
             role = item.get("role")
-            content = item.get("content")
-            if role in {"user", "assistant"} and isinstance(content, str) and content.strip():
-                messages.append({"role": role, "content": content.strip()})
+            content = _message_text(item.get("content"))
+            if role in {"user", "assistant"} and content:
+                messages.append({"role": role, "content": content})
             continue
@@
 def respond(message: str, history: list[dict], temperature: float, top_p: float) -> str:
     model, tokenizer = _load_model()
+    message = _message_text(message)
     messages = [{"role": "system", "content": SYSTEM_PROMPT}]
     messages.extend(_history_to_messages(history))
-    messages.append({"role": "user", "content": message.strip()})
+    messages.append({"role": "user", "content": message})
@@
     def bot_turn(chat_history: list, temperature_value: float, top_p_value: float) -> list:
-        user_message = chat_history[-1]["content"]
+        user_message = _message_text(chat_history[-1]["content"])
         assistant_message = respond(user_message, chat_history[:-1], temperature_value, top_p_value)
         return chat_history + [{"role": "assistant", "content": assistant_message}]
@@
 if __name__ == "__main__":
-    demo.launch(css=CSS, theme=gr.themes.Soft(primary_hue="green", neutral_hue="stone"))
+    demo.launch(
+        css=CSS,
+        theme=gr.themes.Soft(primary_hue="green", neutral_hue="stone"),
+        show_error=True,
+    )
*** End Patch


@@ -47,2 +47,16 @@

+def _message_text(content) -> str:
+    if isinstance(content, str):
+        return content.strip()
+    if isinstance(content, list):
+        parts = []
+        for item in content:
+            if isinstance(item, dict):
+                text = item.get("text")
+                if isinstance(text, str):
+                    parts.append(text)
+        return " ".join(part.strip() for part in parts if part.strip()).strip()
+    return ""
+
+
 def _load_model():
@@ -85,5 +99,5 @@
             role = item.get("role")
-            content = item.get("content")
-            if role in {"user", "assistant"} and isinstance(content, str) and content.strip():
-                messages.append({"role": role, "content": content.strip()})
+            content = _message_text(item.get("content"))
+            if role in {"user", "assistant"} and content:
+                messages.append({"role": role, "content": content})
             continue
@@ -107,5 +121,6 @@
     model, tokenizer = _load_model()
+    message = _message_text(message)
     messages = [{"role": "system", "content": SYSTEM_PROMPT}]
     messages.extend(_history_to_messages(history))
-    messages.append({"role": "user", "content": message.strip()})
+    messages.append({"role": "user", "content": message})

@@ -288,3 +303,3 @@
     def bot_turn(chat_history: list, temperature_value: float, top_p_value: float) -> list:
-        user_message = chat_history[-1]["content"]
+        user_message = _message_text(chat_history[-1]["content"])
         assistant_message = respond(user_message, chat_history[:-1], temperature_value, top_p_value)
@@ -306,2 +321,6 @@
 if __name__ == "__main__":
-    demo.launch(css=CSS, theme=gr.themes.Soft(primary_hue="green", neutral_hue="stone"))
+    demo.launch(
+        css=CSS,
+        theme=gr.themes.Soft(primary_hue="green", neutral_hue="stone"),
+        show_error=True,
+    )


Output:
Exit code: 0
Wall time: 0.1 seconds
Output:
Success. Updated the following files:
M deploy/app.py


Saya re-push normalizer pesan dan akan test API lagi setelah Space RUNNING.


Allow re-uploading the Gradio message-normalization fix and checking runtime?


Output:
Chunk ID: 834ab0
Wall time: 15.0304 seconds
Process exited with code 0
Original token count: 432
Output:
✓ Initialized. View run at
https://modal.com/apps/harisabektidsubrata/main/ap-S5xsJ9H1pYZd6e7uLHp72V
✓ Created objects.
├── 🔨 Created mount
│   /media/haris-subrata/Work/llm/NeuroBait-Build-Small-Model/train/modal_train.
│   py
├── 🔨 Created mount
│   /media/haris-subrata/Work/llm/NeuroBait-Build-Small-Model/deploy
├── 🔨 Created mount model-card/README.md
├── 🔨 Created mount data/eval.jsonl
├── 🔨 Created mount data/train.jsonl
├── 🔨 Created mount train/train_core.py
├── 🔨 Created function preflight.
├── 🔨 Created function train.
├── 🔨 Created function push_lora_to_hub.
├── 🔨 Created function push_space_to_hub.
├── 🔨 Created function set_space_hardware.
├── 🔨 Created function get_space_runtime.
├── 🔨 Created function get_space_logs.
└── 🔨 Created function merge_and_push.
space repo: build-small-hackathon/NeuroBait
space runtime: {
  "repo_id": "build-small-hackathon/NeuroBait",
  "stage": "RUNNING_BUILDING",
  "hardware": "zero-a10g",
  "requested_hardware": "zero-a10g",
  "sleep_time": 172800,
  "raw": {
    "stage": "RUNNING_BUILDING",
    "hardware": {
      "current": "zero-a10g",
      "requested": "zero-a10g"
    },
    "gcTimeout": 172800,
    "replicas": {
      "current": 1,
      "requested": 1
    },
    "devMode": false,
    "domains": [
      {
        "domain": "build-small-hackathon-neurobait.hf.space",
        "stage": "READY"
      }
    ],
    "sha": "2bc1ce730da2f74ca89d9667fb4eefbec325b2f1"
  }
}
Stopping app - local entrypoint completed.
✓ App completed. View run at
https://modal.com/apps/harisabektidsubrata/main/ap-S5xsJ9H1pYZd6e7uLHp72V


HF sedang rolling build ke commit baru. Saya tunggu sampai `RUNNING` dengan SHA terbaru, lalu retry event API.


Output:
Chunk ID: 5e3899
Wall time: 30.0012 seconds
Process running with session ID 66914
Original token count: 0
Output:


Masih menunggu update aktif.


Output:
Chunk ID: 5e1a06
Wall time: 11.4364 seconds
Process exited with code 0
Original token count: 0
Output:


Output:
Chunk ID: c528ab
Wall time: 0.2011 seconds
Process exited with code 0
Original token count: 300
Output:
{"_id":"6a26dd980eccd859eba85b85","id":"build-small-hackathon/NeuroBait","sdk":"gradio","likes":0,"tags":["gradio","region:us"],"private":false,"author":"build-small-hackathon","sha":"e58485d4ba87f14914fcc7f4a205678b97224fde","lastModified":"2026-06-08T15:33:44.000Z","cardData":{"title":"NeuroBait","colorFrom":"green","colorTo":"blue","sdk":"gradio","app_file":"app.py","pinned":false,"license":"apache-2.0","short_description":"ADHD-friendly task initiation with one tiny next move."},"subdomain":"build-small-hackathon-neurobait","gated":false,"disabled":false,"host":"https://build-small-hackathon-neurobait.hf.space","models":["build-small-hackathon/NeuroBait","unsloth/gemma-4-26B-A4B-it"],"runtime":{"stage":"RUNNING","hardware":{"current":"zero-a10g","requested":"zero-a10g"},"gcTimeout":172800,"replicas":{"current":1,"requested":1},"devMode":false,"domains":[{"domain":"build-small-hackathon-neurobait.hf.space","stage":"READY"}],"sha":"e58485d4ba87f14914fcc7f4a205678b97224fde","pySpacesVersion":"0.50.4"},"siblings":[{"rfilename":".gitattributes"},{"rfilename":"README.md"},{"rfilename":"app.py"},{"rfilename":"requirements.txt"}],"createdAt":"2026-06-08T15:19:52.000Z","usedStorage":0}


Runtime sudah RUNNING di commit final. Saya retry inference event sekarang.


Output:
Chunk ID: 5b6e2f
Wall time: 0.9658 seconds
Process exited with code 0
Original token count: 12
Output:
{"event_id":"3926a25d0ced41569cff40f939ac99ae"}


Event diterima lagi. Saya baca stream outputnya; jika model load gagal, sekarang error harus lebih jelas karena `show_error=True`.


curl -s -N https://build-small-hackathon-neurobait.hf.space/gradio_api/call/bot_turn/3926a25d0ced41569cff40f939ac99ae


Output:
Chunk ID: cae6fd
Wall time: 0.9563 seconds
Process exited with code 0
Original token count: 79
Output:
event: error
data: {"error": "1 validation error for ChatbotDataMessages\n0.content\n  Input should be a valid list [type=list_type, input_value='I need to finish a prese...oiding the first slide.', input_type=str]\n    For further information visit https://errors.pydantic.dev/2.12/v/list_type", "visible": true}


Sekarang error jelas: Gradio 6 Chatbot butuh `content` berupa list text blocks. Saya patch output chat history ke format resmi `[{type: text, text: ...}]`.


Input:
*** Begin Patch
*** Update File: deploy/app.py
@@
     def user_turn(user_message: str, chat_history: list) -> tuple[str, list]:
         if not user_message.strip():
             return "", chat_history
-        return "", chat_history + [{"role": "user", "content": user_message.strip()}]
+        content = [{"type": "text", "text": user_message.strip()}]
+        return "", chat_history + [{"role": "user", "content": content}]
@@
         user_message = _message_text(chat_history[-1]["content"])
         assistant_message = respond(user_message, chat_history[:-1], temperature_value, top_p_value)
-        return chat_history + [{"role": "assistant", "content": assistant_message}]
+        content = [{"type": "text", "text": assistant_message}]
+        return chat_history + [{"role": "assistant", "content": content}]
*** End Patch


@@ -300,3 +300,4 @@
             return "", chat_history
-        return "", chat_history + [{"role": "user", "content": user_message.strip()}]
+        content = [{"type": "text", "text": user_message.strip()}]
+        return "", chat_history + [{"role": "user", "content": content}]

@@ -305,3 +306,4 @@
         assistant_message = respond(user_message, chat_history[:-1], temperature_value, top_p_value)
-        return chat_history + [{"role": "assistant", "content": assistant_message}]
+        content = [{"type": "text", "text": assistant_message}]
+        return chat_history + [{"role": "assistant", "content": content}]


Output:
Exit code: 0
Wall time: 0.1 seconds
Output:
Success. Updated the following files:
M deploy/app.py


Saya re-push patch format ChatbotDataMessages, lalu test lagi.


Allow re-uploading the Gradio 6 ChatbotDataMessages format fix and checking runtime?


Output:
Chunk ID: 232d7c
Wall time: 19.6874 seconds
Process exited with code 0
Original token count: 432
Output:
✓ Initialized. View run at
https://modal.com/apps/harisabektidsubrata/main/ap-9VMiOzZ3JdEWrSlmnzUDO9
✓ Created objects.
├── 🔨 Created mount
│   /media/haris-subrata/Work/llm/NeuroBait-Build-Small-Model/train/modal_train.
│   py
├── 🔨 Created mount
│   /media/haris-subrata/Work/llm/NeuroBait-Build-Small-Model/deploy
├── 🔨 Created mount model-card/README.md
├── 🔨 Created mount data/train.jsonl
├── 🔨 Created mount train/train_core.py
├── 🔨 Created mount data/eval.jsonl
├── 🔨 Created function preflight.
├── 🔨 Created function train.
├── 🔨 Created function push_lora_to_hub.
├── 🔨 Created function push_space_to_hub.
├── 🔨 Created function set_space_hardware.
├── 🔨 Created function get_space_runtime.
├── 🔨 Created function get_space_logs.
└── 🔨 Created function merge_and_push.
space repo: build-small-hackathon/NeuroBait
space runtime: {
  "repo_id": "build-small-hackathon/NeuroBait",
  "stage": "RUNNING_BUILDING",
  "hardware": "zero-a10g",
  "requested_hardware": "zero-a10g",
  "sleep_time": 172800,
  "raw": {
    "stage": "RUNNING_BUILDING",
    "hardware": {
      "current": "zero-a10g",
      "requested": "zero-a10g"
    },
    "gcTimeout": 172800,
    "replicas": {
      "current": 1,
      "requested": 1
    },
    "devMode": false,
    "domains": [
      {
        "domain": "build-small-hackathon-neurobait.hf.space",
        "stage": "READY"
      }
    ],
    "sha": "e58485d4ba87f14914fcc7f4a205678b97224fde"
  }
}
Stopping app - local entrypoint completed.
✓ App completed. View run at
https://modal.com/apps/harisabektidsubrata/main/ap-9VMiOzZ3JdEWrSlmnzUDO9


Build final sedang rolling lagi; saya tunggu sampai RUNNING lalu kirim call dengan payload content-list.


Output:
Chunk ID: 33774a
Wall time: 30.0016 seconds
Process running with session ID 1160
Original token count: 0
Output:


Menunggu commit baru aktif di Space.


Output:
Chunk ID: 535060
Wall time: 10.8886 seconds
Process exited with code 0
Original token count: 0
Output:


Output:
Chunk ID: 78a004
Wall time: 0.2808 seconds
Process exited with code 0
Original token count: 300
Output:
{"_id":"6a26dd980eccd859eba85b85","id":"build-small-hackathon/NeuroBait","sdk":"gradio","likes":0,"tags":["gradio","region:us"],"private":false,"author":"build-small-hackathon","sha":"b52dc01b18ffc024074484f86bd36ac1c900ad96","lastModified":"2026-06-08T15:35:25.000Z","cardData":{"title":"NeuroBait","colorFrom":"green","colorTo":"blue","sdk":"gradio","app_file":"app.py","pinned":false,"license":"apache-2.0","short_description":"ADHD-friendly task initiation with one tiny next move."},"subdomain":"build-small-hackathon-neurobait","gated":false,"disabled":false,"host":"https://build-small-hackathon-neurobait.hf.space","models":["build-small-hackathon/NeuroBait","unsloth/gemma-4-26B-A4B-it"],"runtime":{"stage":"RUNNING","hardware":{"current":"zero-a10g","requested":"zero-a10g"},"gcTimeout":172800,"replicas":{"current":1,"requested":1},"devMode":false,"domains":[{"domain":"build-small-hackathon-neurobait.hf.space","stage":"READY"}],"sha":"b52dc01b18ffc024074484f86bd36ac1c900ad96","pySpacesVersion":"0.50.4"},"siblings":[{"rfilename":".gitattributes"},{"rfilename":"README.md"},{"rfilename":"app.py"},{"rfilename":"requirements.txt"}],"createdAt":"2026-06-08T15:19:52.000Z","usedStorage":0}


Space final RUNNING. Saya test inference lagi dengan payload Gradio 6 yang valid.


curl -s -X POST https://build-small-hackathon-neurobait.hf.space/gradio_api/call/bot_turn -H 'Content-Type: application/json' -d '{"data":[[{"role":"user","content":[{"type":"text","text":"I need to finish a presentation tomorrow, but I keep avoiding the first slide."}]}],0.7,0.9]}'


Output:
Chunk ID: c1a823
Wall time: 1.1664 seconds
Process exited with code 0
Original token count: 12
Output:
{"event_id":"a52a14c9637c4efc9c936224a95302ee"}


Event diterima; saya baca hasilnya. Model load pertama bisa lebih lama dari call biasa.


curl -s -N https://build-small-hackathon-neurobait.hf.space/gradio_api/call/bot_turn/a52a14c9637c4efc9c936224a95302ee


Output:
Chunk ID: ecc7cf
Wall time: 0.9755 seconds
Process exited with code 0
Original token count: 43
Output:
event: error
data: {"error": "The requested GPU duration (600s) is larger than the maximum allowed", "duration": 10, "visible": true, "title": "ZeroGPU illegal duration"}


ZeroGPU menolak `duration=300` dengan `xlarge` karena dihitung 2x quota menjadi 600s. Saya turunkan ke `duration=120` untuk xlarge, efektif 240s quota, lalu test ulang.


Input:
*** Begin Patch
*** Update File: deploy/app.py
@@
-@spaces.GPU(duration=300, size="xlarge")
+@spaces.GPU(duration=120, size="xlarge")
 def respond(message: str, history: list[dict], temperature: float, top_p: float) -> str:
*** End Patch


@@ -118,3 +118,3 @@

-@spaces.GPU(duration=300, size="xlarge")
+@spaces.GPU(duration=120, size="xlarge")
 def respond(message: str, history: list[dict], temperature: float, top_p: float) -> str:


Output:
Exit code: 0
Wall time: 0.1 seconds
Output:
Success. Updated the following files:
M deploy/app.py


Input:
*** Begin Patch
*** Update File: deploy/README.md
@@
-LoRA adapter. The `@spaces.GPU` call requests ZeroGPU `xlarge` for the generation
-function because the model is a 26B MoE adapter stack.
+LoRA adapter. The `@spaces.GPU` call requests ZeroGPU `xlarge` with a 120-second
+function window because the model is a 26B MoE adapter stack.
*** End Patch


Success. Updated the following files:
M deploy/README.md

@@ -31,4 +31,4 @@
 The default app path uses 4-bit loading for the base model plus the NeuroBait
-LoRA adapter. The `@spaces.GPU` call requests ZeroGPU `xlarge` for the generation
-function because the model is a 26B MoE adapter stack.
+LoRA adapter. The `@spaces.GPU` call requests ZeroGPU `xlarge` with a 120-second
+function window because the model is a 26B MoE adapter stack.


Output:
Exit code: 0
Wall time: 0.1 seconds
Output:
Success. Updated the following files:
M deploy/README.md


Saya re-push durasi ZeroGPU yang legal dan akan retry inference.


Allow re-uploading the legal ZeroGPU duration setting and checking runtime?


Output:
Chunk ID: 7373ae
Wall time: 16.7893 seconds
Process exited with code 0
Original token count: 432
Output:
✓ Initialized. View run at
https://modal.com/apps/harisabektidsubrata/main/ap-jIt6E4SpNAT3AeM4AgK8wB
✓ Created objects.
├── 🔨 Created mount
│   /media/haris-subrata/Work/llm/NeuroBait-Build-Small-Model/train/modal_train.
│   py
├── 🔨 Created mount
│   /media/haris-subrata/Work/llm/NeuroBait-Build-Small-Model/deploy
├── 🔨 Created mount model-card/README.md
├── 🔨 Created mount data/train.jsonl
├── 🔨 Created mount data/eval.jsonl
├── 🔨 Created mount train/train_core.py
├── 🔨 Created function preflight.
├── 🔨 Created function train.
├── 🔨 Created function push_lora_to_hub.
├── 🔨 Created function push_space_to_hub.
├── 🔨 Created function set_space_hardware.
├── 🔨 Created function get_space_runtime.
├── 🔨 Created function get_space_logs.
└── 🔨 Created function merge_and_push.
space repo: build-small-hackathon/NeuroBait
space runtime: {
  "repo_id": "build-small-hackathon/NeuroBait",
  "stage": "RUNNING_BUILDING",
  "hardware": "zero-a10g",
  "requested_hardware": "zero-a10g",
  "sleep_time": 172800,
  "raw": {
    "stage": "RUNNING_BUILDING",
    "hardware": {
      "current": "zero-a10g",
      "requested": "zero-a10g"
    },
    "gcTimeout": 172800,
    "replicas": {
      "current": 1,
      "requested": 1
    },
    "devMode": false,
    "domains": [
      {
        "domain": "build-small-hackathon-neurobait.hf.space",
        "stage": "READY"
      }
    ],
    "sha": "b52dc01b18ffc024074484f86bd36ac1c900ad96"
  }
}
Stopping app - local entrypoint completed.
✓ App completed. View run at
https://modal.com/apps/harisabektidsubrata/main/ap-jIt6E4SpNAT3AeM4AgK8wB


Build rolling lagi. Saya tunggu sampai commit baru RUNNING.


Output:
Chunk ID: 45e633
Wall time: 30.0008 seconds
Process running with session ID 48608
Original token count: 0
Output:


Menunggu Space selesai rolling update.


Output:
Chunk ID: e60ae7
Wall time: 9.1064 seconds
Process exited with code 0
Original token count: 0
Output:


Output:
Chunk ID: 124016
Wall time: 0.1969 seconds
Process exited with code 0
Original token count: 300
Output:
{"_id":"6a26dd980eccd859eba85b85","id":"build-small-hackathon/NeuroBait","sdk":"gradio","likes":0,"tags":["gradio","region:us"],"private":false,"author":"build-small-hackathon","sha":"9a3e431d7e6478dc8eb4497e01c0e2b1d4540cf1","lastModified":"2026-06-08T15:37:25.000Z","cardData":{"title":"NeuroBait","colorFrom":"green","colorTo":"blue","sdk":"gradio","app_file":"app.py","pinned":false,"license":"apache-2.0","short_description":"ADHD-friendly task initiation with one tiny next move."},"subdomain":"build-small-hackathon-neurobait","gated":false,"disabled":false,"host":"https://build-small-hackathon-neurobait.hf.space","models":["build-small-hackathon/NeuroBait","unsloth/gemma-4-26B-A4B-it"],"runtime":{"stage":"RUNNING","hardware":{"current":"zero-a10g","requested":"zero-a10g"},"gcTimeout":172800,"replicas":{"current":1,"requested":1},"devMode":false,"domains":[{"domain":"build-small-hackathon-neurobait.hf.space","stage":"READY"}],"sha":"9a3e431d7e6478dc8eb4497e01c0e2b1d4540cf1","pySpacesVersion":"0.50.4"},"siblings":[{"rfilename":".gitattributes"},{"rfilename":"README.md"},{"rfilename":"app.py"},{"rfilename":"requirements.txt"}],"createdAt":"2026-06-08T15:19:52.000Z","usedStorage":0}


Runtime final sudah RUNNING. Saya retry inference.


Output:
Chunk ID: 8b8ecf
Wall time: 0.9724 seconds
Process exited with code 0
Original token count: 12
Output:
{"event_id":"389a14f78a6d43229c39bd4e595204d4"}


Event diterima. Saya ambil stream outputnya.


curl -s -N https://build-small-hackathon-neurobait.hf.space/gradio_api/call/bot_turn/389a14f78a6d43229c39bd4e595204d4


Output:
Chunk ID: 2028df
Wall time: 0.9883 seconds
Process exited with code 0
Original token count: 43
Output:
event: error
data: {"error": "The requested GPU duration (240s) is larger than the maximum allowed", "duration": 10, "visible": true, "title": "ZeroGPU illegal duration"}


Max ZeroGPU untuk xlarge ternyata di bawah effective 240s. Saya turunkan lagi ke `duration=60` dengan `xlarge`, effective 120s, sesuai batas umum ZeroGPU.


Input:
*** Begin Patch
*** Update File: deploy/app.py
@@
-@spaces.GPU(duration=120, size="xlarge")
+@spaces.GPU(duration=60, size="xlarge")
 def respond(message: str, history: list[dict], temperature: float, top_p: float) -> str:
*** End Patch


@@ -118,3 +118,3 @@

-@spaces.GPU(duration=120, size="xlarge")
+@spaces.GPU(duration=60, size="xlarge")
 def respond(message: str, history: list[dict], temperature: float, top_p: float) -> str:


Output:
Exit code: 0
Wall time: 0.1 seconds
Output:
Success. Updated the following files:
M deploy/app.py


Input:
*** Begin Patch
*** Update File: deploy/README.md
@@
-LoRA adapter. The `@spaces.GPU` call requests ZeroGPU `xlarge` with a 120-second
-function window because the model is a 26B MoE adapter stack.
+LoRA adapter. The `@spaces.GPU` call requests ZeroGPU `xlarge` with a 60-second
+function window because the model is a 26B MoE adapter stack.
*** End Patch


@@ -31,3 +31,3 @@
 The default app path uses 4-bit loading for the base model plus the NeuroBait
-LoRA adapter. The `@spaces.GPU` call requests ZeroGPU `xlarge` with a 120-second
+LoRA adapter. The `@spaces.GPU` call requests ZeroGPU `xlarge` with a 60-second
 function window because the model is a 26B MoE adapter stack.


Output:
Exit code: 0
Wall time: 0.2 seconds
Output:
Success. Updated the following files:
M deploy/README.md


Saya re-push durasi xlarge yang lebih konservatif dan test lagi.


Allow re-uploading the ZeroGPU 60-second duration setting and checking runtime?


Output:
Chunk ID: 23b512
Wall time: 14.4253 seconds
Process exited with code 0
Original token count: 432
Output:
✓ Initialized. View run at
https://modal.com/apps/harisabektidsubrata/main/ap-xsNTI8SXfTZNlUm2792Nf6
✓ Created objects.
├── 🔨 Created mount
│   /media/haris-subrata/Work/llm/NeuroBait-Build-Small-Model/train/modal_train.
│   py
├── 🔨 Created mount
│   /media/haris-subrata/Work/llm/NeuroBait-Build-Small-Model/deploy
├── 🔨 Created mount data/eval.jsonl
├── 🔨 Created mount train/train_core.py
├── 🔨 Created mount model-card/README.md
├── 🔨 Created mount data/train.jsonl
├── 🔨 Created function preflight.
├── 🔨 Created function train.
├── 🔨 Created function push_lora_to_hub.
├── 🔨 Created function push_space_to_hub.
├── 🔨 Created function set_space_hardware.
├── 🔨 Created function get_space_runtime.
├── 🔨 Created function get_space_logs.
└── 🔨 Created function merge_and_push.
space repo: build-small-hackathon/NeuroBait
space runtime: {
  "repo_id": "build-small-hackathon/NeuroBait",
  "stage": "RUNNING_BUILDING",
  "hardware": "zero-a10g",
  "requested_hardware": "zero-a10g",
  "sleep_time": 172800,
  "raw": {
    "stage": "RUNNING_BUILDING",
    "hardware": {
      "current": "zero-a10g",
      "requested": "zero-a10g"
    },
    "gcTimeout": 172800,
    "replicas": {
      "current": 1,
      "requested": 1
    },
    "devMode": false,
    "domains": [
      {
        "domain": "build-small-hackathon-neurobait.hf.space",
        "stage": "READY"
      }
    ],
    "sha": "9a3e431d7e6478dc8eb4497e01c0e2b1d4540cf1"
  }
}
Stopping app - local entrypoint completed.
✓ App completed. View run at
https://modal.com/apps/harisabektidsubrata/main/ap-xsNTI8SXfTZNlUm2792Nf6


Menunggu rolling build terakhir aktif.


Output:
Chunk ID: cf2ecf
Wall time: 30.0017 seconds
Process running with session ID 9733
Original token count: 0
Output:


Saya lanjutkan poll setelah build aktif.


Output:
Chunk ID: 649df7
Wall time: 11.5085 seconds
Process exited with code 0
Original token count: 0
Output:


Saya cek status Space dan lanjutkan inference kalau sudah RUNNING.


Output:
Chunk ID: acab0d
Wall time: 0.1920 seconds
Process exited with code 0
Original token count: 300
Output:
{"_id":"6a26dd980eccd859eba85b85","id":"build-small-hackathon/NeuroBait","sdk":"gradio","likes":0,"tags":["gradio","region:us"],"private":false,"author":"build-small-hackathon","sha":"69e1281cf017ae4c219fa25ec3ac25386c65c130","lastModified":"2026-06-08T15:39:13.000Z","cardData":{"title":"NeuroBait","colorFrom":"green","colorTo":"blue","sdk":"gradio","app_file":"app.py","pinned":false,"license":"apache-2.0","short_description":"ADHD-friendly task initiation with one tiny next move."},"subdomain":"build-small-hackathon-neurobait","gated":false,"disabled":false,"host":"https://build-small-hackathon-neurobait.hf.space","models":["build-small-hackathon/NeuroBait","unsloth/gemma-4-26B-A4B-it"],"runtime":{"stage":"RUNNING","hardware":{"current":"zero-a10g","requested":"zero-a10g"},"gcTimeout":172800,"replicas":{"current":1,"requested":1},"devMode":false,"domains":[{"domain":"build-small-hackathon-neurobait.hf.space","stage":"READY"}],"sha":"69e1281cf017ae4c219fa25ec3ac25386c65c130","pySpacesVersion":"0.50.4"},"siblings":[{"rfilename":".gitattributes"},{"rfilename":"README.md"},{"rfilename":"app.py"},{"rfilename":"requirements.txt"}],"createdAt":"2026-06-08T15:19:52.000Z","usedStorage":0}


Space RUNNING dengan durasi legal. Saya retry inference event.


Output:
Chunk ID: d15e18
Wall time: 1.0213 seconds
Process exited with code 0
Original token count: 12
Output:
{"event_id":"57ca91afad47415da541cc972a8250bf"}


Event diterima; sekarang saya tunggu hasil generation.


curl -s -N https://build-small-hackathon-neurobait.hf.space/gradio_api/call/bot_turn/57ca91afad47415da541cc972a8250bf


Output:
Chunk ID: 5f1a9b
Wall time: 30.0016 seconds
Process running with session ID 84525
Original token count: 8
Output:
event: heartbeat
data: null


Inference masih berjalan, heartbeat diterima. Ini kemungkinan model sedang load di ZeroGPU. Saya lanjut tunggu stream sampai selesai atau error.


Output:
Chunk ID: 517005
Wall time: 23.0795 seconds
Process exited with code 0
Original token count: 44
Output:
event: heartbeat
data: null

event: heartbeat
data: null

event: error
data: {"error": "GPU task aborted", "duration": 10, "visible": true, "title": "ZeroGPU worker error"}


ZeroGPU accepted the task but worker aborted during model load/generation. Berdasarkan docs ZeroGPU, model sebaiknya ditempatkan di CUDA saat module startup, bukan lazy-load di dalam function GPU. Saya akan ubah loading jadi startup-load untuk ZeroGPU dan turunkan default output token agar inference masuk 60 detik.


Input:
*** Begin Patch
*** Update File: deploy/app.py
@@
-MAX_NEW_TOKENS = int(os.environ.get("MAX_NEW_TOKENS", "260"))
+MAX_NEW_TOKENS = int(os.environ.get("MAX_NEW_TOKENS", "160"))
@@
 def _clean_response(text: str) -> str:
@@
     return text.strip()

+# ZeroGPU recommends placing models on CUDA at module startup. The flag is kept
+# configurable so the same app can still be debugged on non-GPU hardware.
+if os.environ.get("LOAD_AT_STARTUP", "1").lower() not in {"0", "false", "no"}:
+    _load_model()
+
+
 @spaces.GPU(duration=60, size="xlarge")
 def respond(message: str, history: list[dict], temperature: float, top_p: float) -> str:
*** End Patch


@@ -17,3 +17,3 @@
 ADAPTER_ID = os.environ.get("ADAPTER_ID", os.environ.get("MODEL_ID", "build-small-hackathon/NeuroBait"))
-MAX_NEW_TOKENS = int(os.environ.get("MAX_NEW_TOKENS", "260"))
+MAX_NEW_TOKENS = int(os.environ.get("MAX_NEW_TOKENS", "160"))
 LOAD_IN_4BIT = os.environ.get("LOAD_IN_4BIT", "1").lower() not in {"0", "false", "no"}
@@ -118,2 +118,8 @@

+# ZeroGPU recommends placing models on CUDA at module startup. The flag is kept
+# configurable so the same app can still be debugged on non-GPU hardware.
+if os.environ.get("LOAD_AT_STARTUP", "1").lower() not in {"0", "false", "no"}:
+    _load_model()
+
+
 @spaces.GPU(duration=60, size="xlarge")


Output:
Exit code: 0
Wall time: 0.1 seconds
Output:
Success. Updated the following files:
M deploy/app.py


Input:
*** Begin Patch
*** Update File: deploy/README.md
@@
 MAX_NEW_TOKENS=260
+LOAD_AT_STARTUP=1
 ```
*** End Patch


Output:
Exit code: 0
Wall time: 0.1 seconds
Output:
Success. Updated the following files:
M deploy/README.md


Saya koreksi README Space juga agar env default sesuai perubahan token limit/startup load.


Input:
*** Begin Patch
*** Update File: deploy/README.md
@@
-MAX_NEW_TOKENS=260
+MAX_NEW_TOKENS=160
 LOAD_AT_STARTUP=1
*** End Patch


@@ -40,3 +40,3 @@
 LOAD_IN_4BIT=1
-MAX_NEW_TOKENS=260
+MAX_NEW_TOKENS=160
 LOAD_AT_STARTUP=1


Output:
Exit code: 0
Wall time: 0.1 seconds
Output:
Success. Updated the following files:
M deploy/README.md


Saya re-push dengan startup-load. Kali ini status build akan lebih bermakna: kalau model terlalu berat untuk ZeroGPU startup, runtime akan error; kalau RUNNING, inference seharusnya tidak menghabiskan durasi untuk load.


Allow re-uploading the ZeroGPU startup-load deployment variant and checking runtime?


Output:
Chunk ID: de0192
Wall time: 14.1532 seconds
Process exited with code 0
Original token count: 432
Output:
✓ Initialized. View run at
https://modal.com/apps/harisabektidsubrata/main/ap-q8ffp6Wcsy6Qv1hhSSC7X4
✓ Created objects.
├── 🔨 Created mount
│   /media/haris-subrata/Work/llm/NeuroBait-Build-Small-Model/train/modal_train.
│   py
├── 🔨 Created mount
│   /media/haris-subrata/Work/llm/NeuroBait-Build-Small-Model/deploy
├── 🔨 Created mount model-card/README.md
├── 🔨 Created mount train/train_core.py
├── 🔨 Created mount data/eval.jsonl
├── 🔨 Created mount data/train.jsonl
├── 🔨 Created function preflight.
├── 🔨 Created function train.
├── 🔨 Created function push_lora_to_hub.
├── 🔨 Created function push_space_to_hub.
├── 🔨 Created function set_space_hardware.
├── 🔨 Created function get_space_runtime.
├── 🔨 Created function get_space_logs.
└── 🔨 Created function merge_and_push.
space repo: build-small-hackathon/NeuroBait
space runtime: {
  "repo_id": "build-small-hackathon/NeuroBait",
  "stage": "RUNNING_BUILDING",
  "hardware": "zero-a10g",
  "requested_hardware": "zero-a10g",
  "sleep_time": 172800,
  "raw": {
    "stage": "RUNNING_BUILDING",
    "hardware": {
      "current": "zero-a10g",
      "requested": "zero-a10g"
    },
    "gcTimeout": 172800,
    "replicas": {
      "current": 1,
      "requested": 1
    },
    "devMode": false,
    "domains": [
      {
        "domain": "build-small-hackathon-neurobait.hf.space",
        "stage": "READY"
      }
    ],
    "sha": "69e1281cf017ae4c219fa25ec3ac25386c65c130"
  }
}
Stopping app - local entrypoint completed.
✓ App completed. View run at
https://modal.com/apps/harisabektidsubrata/main/ap-q8ffp6Wcsy6Qv1hhSSC7X4


Build sekarang mungkin lebih lama karena startup-load model. Saya beri waktu lebih panjang sebelum cek status.


Output:
Chunk ID: f7c6b9
Wall time: 30.0014 seconds
Process running with session ID 4563
Original token count: 0
Output:


Masih menunggu. Ini expected karena startup sekarang melakukan load model.


Output:
Chunk ID: e76054
Wall time: 30.0013 seconds
Process running with session ID 4563
Original token count: 0
Output:


Startup-load masih berjalan. Saya lanjut satu poll lagi sebelum mengambil status runtime.


Output:
Chunk ID: 14b8b4
Wall time: 19.8782 seconds
Process exited with code 0
Original token count: 0
Output:


Output:
Chunk ID: 65ca8c
Wall time: 0.2079 seconds
Process exited with code 0
Original token count: 303
Output:
{"_id":"6a26dd980eccd859eba85b85","id":"build-small-hackathon/NeuroBait","sdk":"gradio","likes":0,"tags":["gradio","region:us"],"private":false,"author":"build-small-hackathon","sha":"db78e7415ffbe68a25be4e0e5fb5568484a20a25","lastModified":"2026-06-08T15:42:03.000Z","cardData":{"title":"NeuroBait","colorFrom":"green","colorTo":"blue","sdk":"gradio","app_file":"app.py","pinned":false,"license":"apache-2.0","short_description":"ADHD-friendly task initiation with one tiny next move."},"subdomain":"build-small-hackathon-neurobait","gated":false,"disabled":false,"host":"https://build-small-hackathon-neurobait.hf.space","models":["build-small-hackathon/NeuroBait","unsloth/gemma-4-26B-A4B-it"],"runtime":{"stage":"RUNNING_APP_STARTING","hardware":{"current":"zero-a10g","requested":"zero-a10g"},"gcTimeout":172800,"replicas":{"current":1,"requested":1},"devMode":false,"domains":[{"domain":"build-small-hackathon-neurobait.hf.space","stage":"READY"}],"sha":"69e1281cf017ae4c219fa25ec3ac25386c65c130","pySpacesVersion":"0.50.4"},"siblings":[{"rfilename":".gitattributes"},{"rfilename":"README.md"},{"rfilename":"app.py"},{"rfilename":"requirements.txt"}],"createdAt":"2026-06-08T15:19:52.000Z","usedStorage":0}


Runtime `RUNNING_APP_STARTING`: commit baru sudah diterima, container masih mulai app dengan model load. Saya tunggu lagi; kalau berakhir error, kita akan punya keputusan feasibility ZeroGPU.


Output:
Chunk ID: af4235
Wall time: 30.0005 seconds
Process running with session ID 69050
Original token count: 0
Output:


Masih menunggu startup model.


Output:
Chunk ID: e32c41
Wall time: 30.0006 seconds
Process running with session ID 69050
Original token count: 0
Output:


Startup masih belum selesai; saya lanjut tunggu sampai 120 detik penuh.


Output:
Chunk ID: 8256c6
Wall time: 30.0014 seconds
Process running with session ID 69050
Original token count: 0
Output:


Masih berjalan. Saya ambil status setelah sisa jeda ini.


Output:
Chunk ID: 2e0ab7
Wall time: 13.9308 seconds
Process exited with code 0
Original token count: 0
Output:


Output:
Chunk ID: a3b571
Wall time: 0.2639 seconds
Process exited with code 0
Original token count: 814
Output:
{"_id":"6a26dd980eccd859eba85b85","id":"build-small-hackathon/NeuroBait","sdk":"gradio","likes":0,"tags":["gradio","region:us"],"private":false,"author":"build-small-hackathon","sha":"db78e7415ffbe68a25be4e0e5fb5568484a20a25","lastModified":"2026-06-08T15:42:03.000Z","cardData":{"title":"NeuroBait","colorFrom":"green","colorTo":"blue","sdk":"gradio","app_file":"app.py","pinned":false,"license":"apache-2.0","short_description":"ADHD-friendly task initiation with one tiny next move."},"subdomain":"build-small-hackathon-neurobait","gated":false,"disabled":false,"host":"https://build-small-hackathon-neurobait.hf.space","models":["build-small-hackathon/NeuroBait","unsloth/gemma-4-26B-A4B-it"],"runtime":{"stage":"RUNTIME_ERROR","hardware":{"current":null,"requested":"zero-a10g"},"gcTimeout":172800,"errorMessage":"Exit code: 1. Reason: 00<?, ?B/s]\u001b[A\rgeneration_config.json: 100%|██████████| 208/208 [00:00<00:00, 1.43MB/s]\n\n\radapter_config.json:   0%|          | 0.00/1.31k [00:00<?, ?B/s]\u001b[A\radapter_config.json: 100%|██████████| 1.31k/1.31k [00:00<00:00, 9.92MB/s]\nTraceback (most recent call last):\n  File \"/home/user/app/app.py\", line 122, in <module>\n    _load_model()\n  File \"/home/user/app/app.py\", line 87, in _load_model\n    model = PeftModel.from_pretrained(base, ADAPTER_ID, token=HF_TOKEN)\n  File \"/usr/local/lib/python3.10/site-packages/peft/peft_model.py\", line 574, in from_pretrained\n    model = MODEL_TYPE_TO_PEFT_MODEL_MAPPING[config.task_type](\n  File \"/usr/local/lib/python3.10/site-packages/peft/peft_model.py\", line 1955, in __init__\n    super().__init__(model, peft_config, adapter_name, **kwargs)\n  File \"/usr/local/lib/python3.10/site-packages/peft/peft_model.py\", line 129, in __init__\n    self.base_model = cls(model, {adapter_name: peft_config}, adapter_name)\n  File \"/usr/local/lib/python3.10/site-packages/peft/tuners/tuners_utils.py\", line 315, in __init__\n    self.inject_adapter(self.model, adapter_name, low_cpu_mem_usage=low_cpu_mem_usage, state_dict=state_dict)\n  File \"/usr/local/lib/python3.10/site-packages/peft/tuners/tuners_utils.py\", line 913, in inject_adapter\n    self._create_and_replace(\n  File \"/usr/local/lib/python3.10/site-packages/peft/tuners/lora/model.py\", line 269, in _create_and_replace\n    new_module = self._create_new_module(lora_config, adapter_name, target, device_map=device_map, **kwargs)\n  File \"/usr/local/lib/python3.10/site-packages/peft/tuners/lora/model.py\", line 424, in _create_new_module\n    raise ValueError(\nValueError: Target module Gemma4ClippableLinear(\n  (linear): Linear4bit(in_features=1152, out_features=1152, bias=False)\n) is not supported. Currently, only the following modules are supported: `torch.nn.Linear`, `torch.nn.Embedding`, `torch.nn.Conv1d`, `torch.nn.Conv2d`, `torch.nn.Conv3d`, `transformers.pytorch_utils.Conv1D`, `torch.nn.MultiheadAttention.`.\n","replicas":{"requested":1},"devMode":false,"domains":[{"domain":"build-small-hackathon-neurobait.hf.space","stage":"READY"}]},"siblings":[{"rfilename":".gitattributes"},{"rfilename":"README.md"},{"rfilename":"app.py"},{"rfilename":"requirements.txt"}],"createdAt":"2026-06-08T15:19:52.000Z","usedStorage":0}


Feasibility finding penting: Transformers+PEFT 4-bit tidak bisa inject LoRA ke `Gemma4ClippableLinear`. Ini bukan UI issue lagi. Solusi deploy harus pakai Unsloth loader, sama seperti train/eval yang sudah berhasil, karena Unsloth menangani wrapper Gemma 4 tersebut. Saya patch Space ke `FastModel.from_pretrained(adapter_id)` dan update requirements.


Input:
*** Begin Patch
*** Update File: deploy/app.py
@@
 import gradio as gr
 import spaces
 import torch
-from peft import PeftModel
-from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
+from unsloth import FastModel
@@
         if _model is not None and _tokenizer is not None:
             return _model, _tokenizer

-        tokenizer = AutoTokenizer.from_pretrained(ADAPTER_ID, token=HF_TOKEN)
-        quantization_config = None
-        torch_dtype = torch.bfloat16
-        if LOAD_IN_4BIT:
-            quantization_config = BitsAndBytesConfig(
-                load_in_4bit=True,
-                bnb_4bit_compute_dtype=torch.bfloat16,
-                bnb_4bit_quant_type="nf4",
-            )
-            torch_dtype = None
-
-        base = AutoModelForCausalLM.from_pretrained(
-            BASE_MODEL,
-            token=HF_TOKEN,
-            torch_dtype=torch_dtype,
-            quantization_config=quantization_config,
-            device_map="auto",
-        )
-        model = PeftModel.from_pretrained(base, ADAPTER_ID, token=HF_TOKEN)
+        model, tokenizer = FastModel.from_pretrained(
+            model_name=ADAPTER_ID,
+            max_seq_length=2048,
+            load_in_4bit=LOAD_IN_4BIT,
+            load_in_16bit=not LOAD_IN_4BIT,
+            full_finetuning=False,
+        )
+        try:
+            FastModel.for_inference(model)
+        except Exception:
+            pass
         model.eval()
*** End Patch


@@ -11,4 +11,3 @@
 import torch
-from peft import PeftModel
-from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
+from unsloth import FastModel

@@ -67,22 +66,14 @@
             return _model, _tokenizer
-
-        tokenizer = AutoTokenizer.from_pretrained(ADAPTER_ID, token=HF_TOKEN)
-        quantization_config = None
-        torch_dtype = torch.bfloat16
-        if LOAD_IN_4BIT:
-            quantization_config = BitsAndBytesConfig(
-                load_in_4bit=True,
-                bnb_4bit_compute_dtype=torch.bfloat16,
-                bnb_4bit_quant_type="nf4",
-            )
-            torch_dtype = None

-        base = AutoModelForCausalLM.from_pretrained(
-            BASE_MODEL,
-            token=HF_TOKEN,
-            torch_dtype=torch_dtype,
-            quantization_config=quantization_config,
-            device_map="auto",
+        model, tokenizer = FastModel.from_pretrained(
+            model_name=ADAPTER_ID,
+            max_seq_length=2048,
+            load_in_4bit=LOAD_IN_4BIT,
+            load_in_16bit=not LOAD_IN_4BIT,
+            full_finetuning=False,
         )
-        model = PeftModel.from_pretrained(base, ADAPTER_ID, token=HF_TOKEN)
+        try:
+            FastModel.for_inference(model)
+        except Exception:
+            pass
         model.eval()


Output:
Exit code: 0
Wall time: 0.1 seconds
Output:
Success. Updated the following files:
M deploy/app.py


Unsloth loader sudah dipakai. Saya update dependency Space supaya environment punya Unsloth runtime yang sama family-nya dengan Modal eval.


Input:
*** Begin Patch
*** Update File: deploy/requirements.txt
@@
 spaces
 gradio
+unsloth
+unsloth_zoo
 transformers==5.5.0
+trl==0.24
 peft==0.19.1
+datasets
 accelerate
 torch
 bitsandbytes
 huggingface_hub
*** End Patch


Success. Updated the following files:
M deploy/requirements.txt

@@ -2,4 +2,8 @@
 gradio
+unsloth
+unsloth_zoo
 transformers==5.5.0
+trl==0.24
 peft==0.19.1
+datasets
 accelerate


Output:
Exit code: 0
Wall time: 0.1 seconds
Output:
Success. Updated the following files:
M deploy/requirements.txt


Saya perbarui Space README agar tidak lagi menyebut PEFT path; deployment sekarang adapter langsung via Unsloth.


Input:
*** Begin Patch
*** Update File: deploy/README.md
@@
-This Space loads:
+This Space loads through Unsloth:

 - Base model: `unsloth/gemma-4-26b-a4b-it`
 - LoRA adapter: `build-small-hackathon/NeuroBait`
@@
-The default app path uses 4-bit loading for the base model plus the NeuroBait
-LoRA adapter. The `@spaces.GPU` call requests ZeroGPU `xlarge` with a 60-second
-function window because the model is a 26B MoE adapter stack.
+The default app path uses Unsloth 4-bit loading for the NeuroBait LoRA adapter.
+The `@spaces.GPU` call requests ZeroGPU `xlarge` with a 60-second function
+window because the model is a 26B MoE adapter stack.
*** End Patch


@@ -23,3 +23,3 @@

-This Space loads:
+This Space loads through Unsloth:

@@ -30,5 +30,5 @@

-The default app path uses 4-bit loading for the base model plus the NeuroBait
-LoRA adapter. The `@spaces.GPU` call requests ZeroGPU `xlarge` with a 60-second
-function window because the model is a 26B MoE adapter stack.
+The default app path uses Unsloth 4-bit loading for the NeuroBait LoRA adapter.
+The `@spaces.GPU` call requests ZeroGPU `xlarge` with a 60-second function
+window because the model is a 26B MoE adapter stack.


Output:
Exit code: 0
Wall time: 0.1 seconds
Output:
Success. Updated the following files:
M deploy/README.md


Saya re-push Unsloth deployment. Build bisa lebih lama karena install Unsloth, tapi ini loader yang sesuai dengan training/eval yang sudah berhasil di Modal.


Allow re-uploading the Unsloth-based Space deployment and checking runtime?


Output:
Chunk ID: e33015
Wall time: 17.0618 seconds
Process exited with code 0
Original token count: 406
Output:
✓ Initialized. View run at
https://modal.com/apps/harisabektidsubrata/main/ap-MKfkyI6JJhem1Gz9kjFrLu
✓ Created objects.
├── 🔨 Created mount
│   /media/haris-subrata/Work/llm/NeuroBait-Build-Small-Model/train/modal_train.
│   py
├── 🔨 Created mount
│   /media/haris-subrata/Work/llm/NeuroBait-Build-Small-Model/deploy
├── 🔨 Created mount model-card/README.md
├── 🔨 Created mount data/eval.jsonl
├── 🔨 Created mount data/train.jsonl
├── 🔨 Created mount train/train_core.py
├── 🔨 Created function preflight.
├── 🔨 Created function train.
├── 🔨 Created function push_lora_to_hub.
├── 🔨 Created function push_space_to_hub.
├── 🔨 Created function set_space_hardware.
├── 🔨 Created function get_space_runtime.
├── 🔨 Created function get_space_logs.
└── 🔨 Created function merge_and_push.
space repo: build-small-hackathon/NeuroBait
space runtime: {
  "repo_id": "build-small-hackathon/NeuroBait",
  "stage": "BUILDING",
  "hardware": null,
  "requested_hardware": "zero-a10g",
  "sleep_time": 172800,
  "raw": {
    "stage": "BUILDING",
    "hardware": {
      "current": null,
      "requested": "zero-a10g"
    },
    "gcTimeout": 172800,
    "replicas": {
      "requested": 1
    },
    "devMode": false,
    "domains": [
      {
        "domain": "build-small-hackathon-neurobait.hf.space",
        "stage": "READY"
      }
    ]
  }
}
Stopping app - local entrypoint completed.
✓ App completed. View run at
https://modal.com/apps/harisabektidsubrata/main/ap-MKfkyI6JJhem1Gz9kjFrLu


Space sedang rebuild dari awal karena dependency berubah. Saya tunggu lebih lama dan cek error/runtime.


Output:
Chunk ID: c08591
Wall time: 30.0020 seconds
Process running with session ID 87234
Original token count: 0
Output:


Build Unsloth masih berjalan. Ini wajar untuk dependency stack besar.


Output:
Chunk ID: ffa5a5
Wall time: 30.0004 seconds
Process running with session ID 87234
Original token count: 0
Output:


Masih menunggu build dependency.


Output:
Chunk ID: 5c1e7e
Wall time: 30.0008 seconds
Process running with session ID 87234
Original token count: 0
Output:


Build masih belum selesai. Saya lanjut sampai 180 detik penuh.


Output:
Chunk ID: e1d80d
Wall time: 30.0006 seconds
Process running with session ID 87234
Original token count: 0
Output:


Masih berjalan; Unsloth install di Space memang berat.


Output:
Chunk ID: 7e2754
Wall time: 30.0007 seconds
Process running with session ID 87234
Original token count: 0
Output:


Saya ambil status setelah satu interval lagi.


Output:
Chunk ID: 802559
Wall time: 10.5978 seconds
Process exited with code 0
Original token count: 0
Output:


Output:
Chunk ID: 0164c1
Wall time: 0.1904 seconds
Process exited with code 0
Original token count: 278
Output:
{"_id":"6a26dd980eccd859eba85b85","id":"build-small-hackathon/NeuroBait","sdk":"gradio","likes":0,"tags":["gradio","region:us"],"private":false,"author":"build-small-hackathon","sha":"05fcc9369e6caf898b36d8c78bc034e4b5af2e41","lastModified":"2026-06-08T15:46:47.000Z","cardData":{"title":"NeuroBait","colorFrom":"green","colorTo":"blue","sdk":"gradio","app_file":"app.py","pinned":false,"license":"apache-2.0","short_description":"ADHD-friendly task initiation with one tiny next move."},"subdomain":"build-small-hackathon-neurobait","gated":false,"disabled":false,"host":"https://build-small-hackathon-neurobait.hf.space","models":["build-small-hackathon/NeuroBait","unsloth/gemma-4-26B-A4B-it"],"runtime":{"stage":"APP_STARTING","hardware":{"current":null,"requested":"zero-a10g"},"gcTimeout":172800,"replicas":{"requested":1},"devMode":false,"domains":[{"domain":"build-small-hackathon-neurobait.hf.space","stage":"READY"}]},"siblings":[{"rfilename":".gitattributes"},{"rfilename":"README.md"},{"rfilename":"app.py"},{"rfilename":"requirements.txt"}],"createdAt":"2026-06-08T15:19:52.000Z","usedStorage":0}


Build dependency selesai; sekarang `APP_STARTING`, berarti app sedang import/load Unsloth model. Saya tunggu lagi untuk melihat apakah startup berhasil atau error.


Output:
Chunk ID: be89d6
Wall time: 30.0013 seconds
Process running with session ID 33754
Original token count: 0
Output:


Masih startup-load Unsloth.


Output:
Chunk ID: c1f762
Wall time: 30.0014 seconds
Process running with session ID 33754
Original token count: 0
Output:


Startup masih berjalan; saya lanjut tunggu.


Output:
Chunk ID: 0fc971
Wall time: 30.0006 seconds
Process running with session ID 33754
Original token count: 0
Output:


Masih belum ada status akhir; lanjut poll.


Output:
Chunk ID: 71b4d5
Wall time: 30.0010 seconds
Process running with session ID 33754
Original token count: 0
Output:


Unsloth startup masih panjang. Saya tunggu sampai interval selesai lalu cek runtime.


Output:
Chunk ID: 8c0d3e
Wall time: 30.0007 seconds
Process running with session ID 33754
Original token count: 0
Output:


Satu interval lagi sebelum cek status.


Output:
Chunk ID: e49486
Wall time: 5.9997 seconds
Process exited with code 0
Original token count: 0
Output:


Output:
Chunk ID: d806b3
Wall time: 0.2067 seconds
Process exited with code 0
Original token count: 782
Output:
{"_id":"6a26dd980eccd859eba85b85","id":"build-small-hackathon/NeuroBait","sdk":"gradio","likes":0,"tags":["gradio","region:us"],"private":false,"author":"build-small-hackathon","sha":"05fcc9369e6caf898b36d8c78bc034e4b5af2e41","lastModified":"2026-06-08T15:46:47.000Z","cardData":{"title":"NeuroBait","colorFrom":"green","colorTo":"blue","sdk":"gradio","app_file":"app.py","pinned":false,"license":"apache-2.0","short_description":"ADHD-friendly task initiation with one tiny next move."},"subdomain":"build-small-hackathon-neurobait","gated":false,"disabled":false,"host":"https://build-small-hackathon-neurobait.hf.space","models":["build-small-hackathon/NeuroBait","unsloth/gemma-4-26B-A4B-it"],"runtime":{"stage":"RUNTIME_ERROR","hardware":{"current":null,"requested":"zero-a10g"},"gcTimeout":172800,"errorMessage":"Exit code: 1. Reason: 🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\nUnsloth: Your Flash Attention 2 installation seems to be broken. Using Xformers instead. No performance changes will be seen.\n🦥 Unsloth Zoo will now patch everything to make training faster!\nTraceback (most recent call last):\n  File \"/home/user/app/app.py\", line 12, in <module>\n    from unsloth import FastModel\n  File \"/usr/local/lib/python3.10/site-packages/unsloth/__init__.py\", line 165, in <module>\n    from ._gpu_init import *\n  File \"/usr/local/lib/python3.10/site-packages/unsloth/_gpu_init.py\", line 334, in <module>\n    from .models import *\n  File \"/usr/local/lib/python3.10/site-packages/unsloth/models/__init__.py\", line 15, in <module>\n    from .llama import FastLlamaModel\n  File \"/usr/local/lib/python3.10/site-packages/unsloth/models/llama.py\", line 77, in <module>\n    from ..kernels import *\n  File \"/usr/local/lib/python3.10/site-packages/unsloth/kernels/__init__.py\", line 15, in <module>\n    from .cross_entropy_loss import (\n  File \"/usr/local/lib/python3.10/site-packages/unsloth/kernels/cross_entropy_loss.py\", line 18, in <module>\n    from .utils import (\n  File \"/usr/local/lib/python3.10/site-packages/unsloth/kernels/utils.py\", line 221, in <module>\n    _CUDA_STREAMS = {\n  File \"/usr/local/lib/python3.10/site-packages/unsloth/kernels/utils.py\", line 223, in <dictcomp>\n    torch._C._cuda_getCurrentRawStream(index)\ntorch.AcceleratorError: CUDA error: no CUDA-capable device is detected\nSearch for `cudaErrorNoDevice' in https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__TYPES.html for more information.\nCUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\nFor debugging consider passing CUDA_LAUNCH_BLOCKING=1\nDevice-side assertions were explicitly omitted for this error check; the error probably arose while initializing the DSA handlers.\n","replicas":{"requested":1},"devMode":false,"domains":[{"domain":"build-small-hackathon-neurobait.hf.space","stage":"READY"}]},"siblings":[{"rfilename":".gitattributes"},{"rfilename":"README.md"},{"rfilename":"app.py"},{"rfilename":"requirements.txt"}],"createdAt":"2026-06-08T15:19:52.000Z","usedStorage":0}


Unsloth tidak bisa di-import saat module startup di ZeroGPU karena belum ada real CUDA saat import; jadi kebalikan dari PEFT case. Saya akan lazy-import Unsloth di dalam function GPU, dan set `LOAD_AT_STARTUP=0`. Ini mungkin masih berat untuk 60 detik, tapi ini satu-satunya path yang cocok dengan Unsloth+ZeroGPU tanpa paid GPU.


Input:
*** Begin Patch
*** Update File: deploy/app.py
@@
 import gradio as gr
 import spaces
 import torch
-from unsloth import FastModel
@@
         if _model is not None and _tokenizer is not None:
             return _model, _tokenizer

+        from unsloth import FastModel
+
@@
-if os.environ.get("LOAD_AT_STARTUP", "1").lower() not in {"0", "false", "no"}:
+if os.environ.get("LOAD_AT_STARTUP", "0").lower() not in {"0", "false", "no"}:
     _load_model()
*** End Patch


@@ -11,3 +11,2 @@
 import torch
-from unsloth import FastModel

@@ -67,2 +66,4 @@

+        from unsloth import FastModel
+
         model, tokenizer = FastModel.from_pretrained(
@@ -111,3 +112,3 @@
 # configurable so the same app can still be debugged on non-GPU hardware.
-if os.environ.get("LOAD_AT_STARTUP", "1").lower() not in {"0", "false", "no"}:
+if os.environ.get("LOAD_AT_STARTUP", "0").lower() not in {"0", "false", "no"}:
     _load_model()


Output:
Exit code: 0
Wall time: 0.3 seconds
Output:
Success. Updated the following files:
M deploy/app.py


Input:
*** Begin Patch
*** Update File: deploy/README.md
@@
-LOAD_AT_STARTUP=1
+LOAD_AT_STARTUP=0
 ```
*** End Patch


@@ -41,3 +41,3 @@
 MAX_NEW_TOKENS=160
-LOAD_AT_STARTUP=1
+LOAD_AT_STARTUP=0
 ```