Text Generation
Transformers
Safetensors
qwen3_5
image-text-to-text
qwen3
code-review
code-analysis
lora
sft
abliterated
multi-token-prediction
reasoning
mtp
conversational
Instructions to use hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview") model = AutoModelForMultimodalLM.from_pretrained("hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview", device_map="auto") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview
- SGLang
How to use hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview with Docker Model Runner:
docker model run hf.co/hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview
Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- README.md +96 -0
- chat_template.jinja +170 -0
- config.json +144 -0
- generation_config.json +13 -0
- model-00001-of-00012.safetensors +3 -0
- model-00002-of-00012.safetensors +3 -0
- model-00003-of-00012.safetensors +3 -0
- model-00004-of-00012.safetensors +3 -0
- model-00005-of-00012.safetensors +3 -0
- model-00006-of-00012.safetensors +3 -0
- model-00007-of-00012.safetensors +3 -0
- model-00008-of-00012.safetensors +3 -0
- model-00009-of-00012.safetensors +3 -0
- model-00010-of-00012.safetensors +3 -0
- model-00011-of-00012.safetensors +3 -0
- model-00012-of-00012.safetensors +3 -0
- model.safetensors.index.json +0 -0
- processor_config.json +60 -0
- tokenizer.json +3 -0
- tokenizer_config.json +34 -0
.gitattributes
CHANGED
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
ADDED
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@@ -0,0 +1,96 @@
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| 1 |
+
---
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| 2 |
+
base_model:
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| 3 |
+
- hotdogs/Qwen3.8-27B-abliterated
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| 4 |
+
datasets:
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| 5 |
+
- hotdogs/code-analysis-sft-qwen38-v2
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| 6 |
+
library_name: transformers
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| 7 |
+
model_type: qwen3_5
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| 8 |
+
pipeline_tag: text-generation
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| 9 |
+
tags:
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| 10 |
+
- qwen3
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| 11 |
+
- code-review
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| 12 |
+
- code-analysis
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| 13 |
+
- lora
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| 14 |
+
- sft
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| 15 |
+
- abliterated
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| 16 |
+
- multi-token-prediction
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| 17 |
+
- reasoning
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| 18 |
+
- mtp
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| 19 |
+
license: mit
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| 20 |
+
---
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| 21 |
+
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| 22 |
+
# Qwen3.8-27B Code Analysis Preview (v2)
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| 23 |
+
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| 24 |
+
A **code-analysis / code-review** fine-tune of [`hotdogs/Qwen3.8-27B-abliterated`](https://huggingface.co/hotdogs/Qwen3.8-27B-abliterated), trained on the **v2 dataset** that fixes the *template-collapse* problem of v1.
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| 25 |
+
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| 26 |
+
Given a snippet of code, it produces a **structured, multi-paragraph review** — real bugs found, line-level reasoning, severity, and a concrete fix in a code block. It is a **reasoning model**: it thinks first (separated into `reasoning_content` when served) and then answers.
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| 27 |
+
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| 28 |
+
> **v1 → v2:** v1 was trained on a synthetic placeholder dataset (15 unique code bodies, 29–44 char answers like `## Review\n\nFound N issue(s) in L lines.`). The model faithfully reproduced the template — it answered *"No bugs found. Code is clean."* and missed real bugs. **v2** was retrained on 21,009 **real** code+bug+answer rows across 5 languages with 550–880 char detailed answers. The model now actually *finds* the bugs.
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| 29 |
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## Highlights
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| 31 |
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- ✅ **Finds real bugs** — off-by-one, missing cache-hit, `fetch` not checking `res.ok`, async races, etc.
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| 33 |
+
- ✅ **Generalizes** — correctly analyzes bug types *not* in the training archetypes (base model supplies the code knowledge; the LoRA supplies the review structure)
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| 34 |
+
- ✅ **No hallucination** on clean code — says *"correct, no bugs"* instead of inventing problems
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| 35 |
+
- ✅ **Reasoning separated** — internal monologue goes to `reasoning_content`, user sees only the answer
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| 36 |
+
- ✅ **MTP preserved** — 15 multi-token-prediction tensors (`mtp.*` / `blk.64.nextn.*`) kept for speculative decoding
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| 37 |
+
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| 38 |
+
## How it was made
|
| 39 |
+
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| 40 |
+
| Step | Detail |
|
| 41 |
+
|---|---|
|
| 42 |
+
| Base | `hotdogs/Qwen3.8-27B-abliterated` (abliterated, ~27B) |
|
| 43 |
+
| Method | Unsloth LoRA, **r=32**, 233M trainable params (0.85%) |
|
| 44 |
+
| Dataset | [`hotdogs/code-analysis-sft-qwen38-v2`](https://huggingface.co/datasets/hotdogs/code-analysis-sft-qwen38-v2) — 21,009 train / 1,900 valid |
|
| 45 |
+
| Languages | Python, JavaScript, Go, Rust, C |
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| 46 |
+
| Answer style | 550–880 chars, line numbers, severity, fix code block |
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| 47 |
+
| Sequence | max 2048 tokens, bf16, 5× RTX 3090 |
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| 48 |
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| Early stop | step 400 / 1313 (epoch ~0.30, loss ~0.0003) — stopped before the 15 archetypes were memorized to death |
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| 49 |
+
| Merge | `merge_and_unload`, MTP 15 tensors recovered, no triple-nest |
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| 50 |
+
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| 51 |
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## Smoke test (v2)
|
| 52 |
+
|
| 53 |
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| Case | Result |
|
| 54 |
+
|---|---|
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| 55 |
+
| Off-by-one (in-archetype) | 🟢 Found it + fix + docstring note |
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| 56 |
+
| Async race (unseen) | 🟢 "no cache-hit fast path" + concurrency |
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| 57 |
+
| Clean code (hallucination test) | 🟢 "correct, no bugs" + minor float/bool note |
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| 58 |
+
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| 59 |
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## Usage (transformers)
|
| 60 |
+
|
| 61 |
+
```python
|
| 62 |
+
from transformers import AutoModelForImageTextToText, AutoTokenizer
|
| 63 |
+
import torch
|
| 64 |
+
|
| 65 |
+
MODEL = "hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview"
|
| 66 |
+
tok = AutoTokenizer.from_pretrained(MODEL, trust_remote_code=True)
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| 67 |
+
model = AutoModelForImageTextToText.from_pretrained(
|
| 68 |
+
MODEL, torch_dtype=torch.bfloat16,
|
| 69 |
+
device_map="auto", trust_remote_code=True, attn_implementation="sdpa")
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| 70 |
+
model.eval()
|
| 71 |
+
|
| 72 |
+
def review(code, max_new=600):
|
| 73 |
+
text = tok.apply_chat_template(
|
| 74 |
+
[{"role": "user", "content": "Review this code and report any bugs you find.\n\n```python\n" + code + "\n```"}],
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| 75 |
+
tokenize=False, add_generation_prompt=True)
|
| 76 |
+
inputs = tok(text, return_tensors="pt").to(model.device)
|
| 77 |
+
with torch.no_grad():
|
| 78 |
+
out = model.generate(input_ids=inputs["input_ids"],
|
| 79 |
+
attention_mask=inputs["attention_mask"],
|
| 80 |
+
max_new_tokens=max_new, do_sample=False,
|
| 81 |
+
repetition_penalty=1.05)
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| 82 |
+
new = out[0][inputs["input_ids"].shape[1]:]
|
| 83 |
+
return tok.decode(new, skip_special_tokens=True)
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| 84 |
+
```
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| 85 |
+
|
| 86 |
+
## Usage (GGUF)
|
| 87 |
+
|
| 88 |
+
See the GGUF repo → [`hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview-mtp-GGUF`](https://huggingface.co/hotdogs/Qwen3.8-27B-abliterated-code-analysis-preview-mtp-GGUF)
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| 89 |
+
|
| 90 |
+
## Files
|
| 91 |
+
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| 92 |
+
12 safetensors shards (~52 GB, bf16) + tokenizer, processor, config, chat template, generation config. 1,199 tensors incl. 15 MTP.
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| 93 |
+
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| 94 |
+
## License
|
| 95 |
+
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| 96 |
+
MIT (inherits the abliterated base).
|
chat_template.jinja
ADDED
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@@ -0,0 +1,170 @@
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| 1 |
+
{%- set image_count = namespace(value=0) %}
|
| 2 |
+
{%- set video_count = namespace(value=0) %}
|
| 3 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
|
| 4 |
+
{%- if content is string %}
|
| 5 |
+
{{- content }}
|
| 6 |
+
{%- elif content is iterable and content is not mapping %}
|
| 7 |
+
{%- for item in content %}
|
| 8 |
+
{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
|
| 9 |
+
{%- if is_system_content %}
|
| 10 |
+
{{- raise_exception('System message cannot contain images.') }}
|
| 11 |
+
{%- endif %}
|
| 12 |
+
{%- if do_vision_count %}
|
| 13 |
+
{%- set image_count.value = image_count.value + 1 %}
|
| 14 |
+
{%- endif %}
|
| 15 |
+
{%- if add_vision_id %}
|
| 16 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
|
| 17 |
+
{%- endif %}
|
| 18 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
|
| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
|
| 20 |
+
{%- if is_system_content %}
|
| 21 |
+
{{- raise_exception('System message cannot contain videos.') }}
|
| 22 |
+
{%- endif %}
|
| 23 |
+
{%- if do_vision_count %}
|
| 24 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 25 |
+
{%- endif %}
|
| 26 |
+
{%- if add_vision_id %}
|
| 27 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
|
| 28 |
+
{%- endif %}
|
| 29 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
|
| 30 |
+
{%- elif 'text' in item %}
|
| 31 |
+
{{- item.text }}
|
| 32 |
+
{%- else %}
|
| 33 |
+
{{- raise_exception('Unexpected item type in content.') }}
|
| 34 |
+
{%- endif %}
|
| 35 |
+
{%- endfor %}
|
| 36 |
+
{%- elif content is none or content is undefined %}
|
| 37 |
+
{{- '' }}
|
| 38 |
+
{%- else %}
|
| 39 |
+
{{- raise_exception('Unexpected content type.') }}
|
| 40 |
+
{%- endif %}
|
| 41 |
+
{%- endmacro %}
|
| 42 |
+
{%- if not messages %}
|
| 43 |
+
{{- raise_exception('No messages provided.') }}
|
| 44 |
+
{%- endif %}
|
| 45 |
+
{%- set reasoning_instructions = '' %}
|
| 46 |
+
{%- if enable_thinking is undefined or enable_thinking is true %}
|
| 47 |
+
{%- set resolved_reasoning_effort = reasoning_effort|default('xhigh') %}
|
| 48 |
+
{%- if resolved_reasoning_effort not in ('xhigh', 'medium', 'low') %}
|
| 49 |
+
{{- raise_exception('Unexpected reasoning effort ' ~ reasoning_effort ~ '. Supported types are xhigh (default), medium, and low.') }}
|
| 50 |
+
{%- endif %}
|
| 51 |
+
{%- if resolved_reasoning_effort == 'xhigh' %}
|
| 52 |
+
{%- set reasoning_instructions = 'Reasoning effort is set to xhigh. Please think carefully through the task, validate key assumptions, consider plausible alternatives, and prioritize correctness, consistency, and clarity in the final answer.' %}
|
| 53 |
+
{%- elif resolved_reasoning_effort == 'low' %}
|
| 54 |
+
{%- set reasoning_instructions = 'Reasoning effort is set to low. Keep your thinking brief and focused, moving directly to the conclusion without unnecessary elaboration.' %}
|
| 55 |
+
{%- endif %}
|
| 56 |
+
{%- endif %}
|
| 57 |
+
{%- if tools and tools is iterable and tools is not mapping %}
|
| 58 |
+
{{- '<|im_start|>system\n' }}
|
| 59 |
+
{%- if reasoning_instructions %}
|
| 60 |
+
{{- reasoning_instructions + '\n\n' }}
|
| 61 |
+
{%- endif %}
|
| 62 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
|
| 63 |
+
{%- for tool in tools %}
|
| 64 |
+
{{- "\n" }}
|
| 65 |
+
{{- tool | tojson }}
|
| 66 |
+
{%- endfor %}
|
| 67 |
+
{{- "\n</tools>" }}
|
| 68 |
+
{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
|
| 69 |
+
{%- if messages[0].role == 'system' %}
|
| 70 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 71 |
+
{%- if content %}
|
| 72 |
+
{{- '\n\n' + content }}
|
| 73 |
+
{%- endif %}
|
| 74 |
+
{%- endif %}
|
| 75 |
+
{{- '<|im_end|>\n' }}
|
| 76 |
+
{%- else %}
|
| 77 |
+
{%- if messages[0].role == 'system' %}
|
| 78 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 79 |
+
{%- if content %}
|
| 80 |
+
{{- '<|im_start|>system\n' + (reasoning_instructions + '\n\n' if reasoning_instructions else '') + content + '<|im_end|>\n' }}
|
| 81 |
+
{%- elif reasoning_instructions %}
|
| 82 |
+
{{- '<|im_start|>system\n' + reasoning_instructions + '<|im_end|>\n' }}
|
| 83 |
+
{%- endif %}
|
| 84 |
+
{%- elif reasoning_instructions %}
|
| 85 |
+
{{- '<|im_start|>system\n' + reasoning_instructions + '<|im_end|>\n' }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- endif %}
|
| 88 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 89 |
+
{%- for message in messages[::-1] %}
|
| 90 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 91 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
|
| 92 |
+
{%- set content = render_content(message.content, false)|trim %}
|
| 93 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 94 |
+
{%- set ns.multi_step_tool = false %}
|
| 95 |
+
{%- set ns.last_query_index = index %}
|
| 96 |
+
{%- endif %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endfor %}
|
| 99 |
+
{%- if ns.multi_step_tool %}
|
| 100 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 101 |
+
{%- endif %}
|
| 102 |
+
{%- for message in messages %}
|
| 103 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 104 |
+
{%- if message.role == "system" %}
|
| 105 |
+
{%- if not loop.first %}
|
| 106 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 107 |
+
{%- endif %}
|
| 108 |
+
{%- elif message.role == "user" %}
|
| 109 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 110 |
+
{%- elif message.role == "assistant" %}
|
| 111 |
+
{%- set reasoning_content = '' %}
|
| 112 |
+
{%- if message.reasoning_content is string %}
|
| 113 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 114 |
+
{%- endif %}
|
| 115 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 116 |
+
{%- if preserve_thinking is undefined or preserve_thinking is true or loop.index0 > ns.last_query_index %}
|
| 117 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 118 |
+
{%- else %}
|
| 119 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 120 |
+
{%- endif %}
|
| 121 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 122 |
+
{%- for tool_call in message.tool_calls %}
|
| 123 |
+
{%- if tool_call.function is defined %}
|
| 124 |
+
{%- set tool_call = tool_call.function %}
|
| 125 |
+
{%- endif %}
|
| 126 |
+
{%- if loop.first %}
|
| 127 |
+
{%- if content|trim %}
|
| 128 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 129 |
+
{%- else %}
|
| 130 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 131 |
+
{%- endif %}
|
| 132 |
+
{%- else %}
|
| 133 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{%- if tool_call.arguments is defined and tool_call.arguments != '' %}
|
| 136 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 137 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 138 |
+
{%- set args_value = args_value | string if args_value is string else args_value | tojson | safe %}
|
| 139 |
+
{{- args_value }}
|
| 140 |
+
{{- '\n</parameter>\n' }}
|
| 141 |
+
{%- endfor %}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{{- '</function>\n</tool_call>' }}
|
| 144 |
+
{%- endfor %}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{{- '<|im_end|>\n' }}
|
| 147 |
+
{%- elif message.role == "tool" %}
|
| 148 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 149 |
+
{{- '<|im_start|>user' }}
|
| 150 |
+
{%- endif %}
|
| 151 |
+
{{- '\n<tool_response>\n' }}
|
| 152 |
+
{{- content }}
|
| 153 |
+
{{- '\n</tool_response>' }}
|
| 154 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 155 |
+
{{- '<|im_end|>\n' }}
|
| 156 |
+
{%- elif loop.last %}
|
| 157 |
+
{{- '<|im_end|>\n' }}
|
| 158 |
+
{%- endif %}
|
| 159 |
+
{%- else %}
|
| 160 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 161 |
+
{%- endif %}
|
| 162 |
+
{%- endfor %}
|
| 163 |
+
{%- if add_generation_prompt %}
|
| 164 |
+
{{- '<|im_start|>assistant\n' }}
|
| 165 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 166 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 167 |
+
{%- else %}
|
| 168 |
+
{{- '<think>\n' }}
|
| 169 |
+
{%- endif %}
|
| 170 |
+
{%- endif %}
|
config.json
ADDED
|
@@ -0,0 +1,144 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"Qwen3_5ForConditionalGeneration"
|
| 4 |
+
],
|
| 5 |
+
"dtype": "bfloat16",
|
| 6 |
+
"image_token_id": 248056,
|
| 7 |
+
"language_model_only": false,
|
| 8 |
+
"model_type": "qwen3_5",
|
| 9 |
+
"pad_token_id": 248044,
|
| 10 |
+
"text_config": {
|
| 11 |
+
"attention_bias": false,
|
| 12 |
+
"attention_dropout": 0.0,
|
| 13 |
+
"attn_output_gate": true,
|
| 14 |
+
"bos_token_id": 248044,
|
| 15 |
+
"dtype": "bfloat16",
|
| 16 |
+
"eos_token_id": 248044,
|
| 17 |
+
"full_attention_interval": 4,
|
| 18 |
+
"head_dim": 256,
|
| 19 |
+
"hidden_act": "silu",
|
| 20 |
+
"hidden_size": 5120,
|
| 21 |
+
"initializer_range": 0.02,
|
| 22 |
+
"intermediate_size": 17408,
|
| 23 |
+
"layer_types": [
|
| 24 |
+
"linear_attention",
|
| 25 |
+
"linear_attention",
|
| 26 |
+
"linear_attention",
|
| 27 |
+
"full_attention",
|
| 28 |
+
"linear_attention",
|
| 29 |
+
"linear_attention",
|
| 30 |
+
"linear_attention",
|
| 31 |
+
"full_attention",
|
| 32 |
+
"linear_attention",
|
| 33 |
+
"linear_attention",
|
| 34 |
+
"linear_attention",
|
| 35 |
+
"full_attention",
|
| 36 |
+
"linear_attention",
|
| 37 |
+
"linear_attention",
|
| 38 |
+
"linear_attention",
|
| 39 |
+
"full_attention",
|
| 40 |
+
"linear_attention",
|
| 41 |
+
"linear_attention",
|
| 42 |
+
"linear_attention",
|
| 43 |
+
"full_attention",
|
| 44 |
+
"linear_attention",
|
| 45 |
+
"linear_attention",
|
| 46 |
+
"linear_attention",
|
| 47 |
+
"full_attention",
|
| 48 |
+
"linear_attention",
|
| 49 |
+
"linear_attention",
|
| 50 |
+
"linear_attention",
|
| 51 |
+
"full_attention",
|
| 52 |
+
"linear_attention",
|
| 53 |
+
"linear_attention",
|
| 54 |
+
"linear_attention",
|
| 55 |
+
"full_attention",
|
| 56 |
+
"linear_attention",
|
| 57 |
+
"linear_attention",
|
| 58 |
+
"linear_attention",
|
| 59 |
+
"full_attention",
|
| 60 |
+
"linear_attention",
|
| 61 |
+
"linear_attention",
|
| 62 |
+
"linear_attention",
|
| 63 |
+
"full_attention",
|
| 64 |
+
"linear_attention",
|
| 65 |
+
"linear_attention",
|
| 66 |
+
"linear_attention",
|
| 67 |
+
"full_attention",
|
| 68 |
+
"linear_attention",
|
| 69 |
+
"linear_attention",
|
| 70 |
+
"linear_attention",
|
| 71 |
+
"full_attention",
|
| 72 |
+
"linear_attention",
|
| 73 |
+
"linear_attention",
|
| 74 |
+
"linear_attention",
|
| 75 |
+
"full_attention",
|
| 76 |
+
"linear_attention",
|
| 77 |
+
"linear_attention",
|
| 78 |
+
"linear_attention",
|
| 79 |
+
"full_attention",
|
| 80 |
+
"linear_attention",
|
| 81 |
+
"linear_attention",
|
| 82 |
+
"linear_attention",
|
| 83 |
+
"full_attention",
|
| 84 |
+
"linear_attention",
|
| 85 |
+
"linear_attention",
|
| 86 |
+
"linear_attention",
|
| 87 |
+
"full_attention"
|
| 88 |
+
],
|
| 89 |
+
"linear_conv_kernel_dim": 4,
|
| 90 |
+
"linear_key_head_dim": 128,
|
| 91 |
+
"linear_num_key_heads": 16,
|
| 92 |
+
"linear_num_value_heads": 48,
|
| 93 |
+
"linear_value_head_dim": 128,
|
| 94 |
+
"mamba_ssm_dtype": "float32",
|
| 95 |
+
"max_position_embeddings": 262144,
|
| 96 |
+
"model_type": "qwen3_5_text",
|
| 97 |
+
"mtp_num_hidden_layers": 1,
|
| 98 |
+
"mtp_use_dedicated_embeddings": false,
|
| 99 |
+
"num_attention_heads": 24,
|
| 100 |
+
"num_hidden_layers": 64,
|
| 101 |
+
"num_key_value_heads": 4,
|
| 102 |
+
"output_gate_type": "swish",
|
| 103 |
+
"pad_token_id": null,
|
| 104 |
+
"partial_rotary_factor": 0.25,
|
| 105 |
+
"rms_norm_eps": 1e-06,
|
| 106 |
+
"rope_parameters": {
|
| 107 |
+
"mrope_interleaved": true,
|
| 108 |
+
"mrope_section": [
|
| 109 |
+
11,
|
| 110 |
+
11,
|
| 111 |
+
10
|
| 112 |
+
],
|
| 113 |
+
"partial_rotary_factor": 0.25,
|
| 114 |
+
"rope_theta": 10000000,
|
| 115 |
+
"rope_type": "default"
|
| 116 |
+
},
|
| 117 |
+
"tie_word_embeddings": false,
|
| 118 |
+
"use_cache": true,
|
| 119 |
+
"vocab_size": 248320
|
| 120 |
+
},
|
| 121 |
+
"tie_word_embeddings": false,
|
| 122 |
+
"transformers_version": "5.14.1",
|
| 123 |
+
"unsloth_version": "2025.11.1",
|
| 124 |
+
"video_token_id": 248057,
|
| 125 |
+
"vision_config": {
|
| 126 |
+
"deepstack_visual_indexes": [],
|
| 127 |
+
"depth": 27,
|
| 128 |
+
"dtype": "bfloat16",
|
| 129 |
+
"hidden_act": "gelu_pytorch_tanh",
|
| 130 |
+
"hidden_size": 1152,
|
| 131 |
+
"in_channels": 3,
|
| 132 |
+
"initializer_range": 0.02,
|
| 133 |
+
"intermediate_size": 4304,
|
| 134 |
+
"model_type": "qwen3_5_vision",
|
| 135 |
+
"num_heads": 16,
|
| 136 |
+
"num_position_embeddings": 2304,
|
| 137 |
+
"out_hidden_size": 5120,
|
| 138 |
+
"patch_size": 16,
|
| 139 |
+
"spatial_merge_size": 2,
|
| 140 |
+
"temporal_patch_size": 2
|
| 141 |
+
},
|
| 142 |
+
"vision_end_token_id": 248054,
|
| 143 |
+
"vision_start_token_id": 248053
|
| 144 |
+
}
|
generation_config.json
ADDED
|
@@ -0,0 +1,13 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token_id": 248044,
|
| 3 |
+
"do_sample": true,
|
| 4 |
+
"eos_token_id": [
|
| 5 |
+
248046,
|
| 6 |
+
248044
|
| 7 |
+
],
|
| 8 |
+
"pad_token_id": 248044,
|
| 9 |
+
"temperature": 1.0,
|
| 10 |
+
"top_k": 20,
|
| 11 |
+
"top_p": 0.95,
|
| 12 |
+
"transformers_version": "5.14.1"
|
| 13 |
+
}
|
model-00001-of-00012.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:54d83c1d36631de231876217a8e0c2483eccee8746369a482b79442bdfc5d958
|
| 3 |
+
size 2542796928
|
model-00002-of-00012.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
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tokenizer_config.json
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"processor_class": "Qwen3VLProcessor",
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