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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,88 @@
+---
+language:
+- en
+license: apache-2.0
+library_name: peft
+base_model: Qwen/Qwen2.5-3B-Instruct
+tags:
+- clinical
+- extraction
+- medical
+- qlora
+- lora
+- healthcare
+- on-prem
+datasets:
+- synthea
+pipeline_tag: text-generation
+---
+
+# Mira-1 — Clinical Extraction SLM
+
+**Enterprise-grade clinical document extraction model.** Fine-tuned from Qwen2.5-3B-Instruct with QLoRA to extract structured JSON from clinical documents (lab reports, discharge summaries, medication lists, pathology reports, intake forms, progress notes).
+
+## Key Features
+
+- **Structured JSON output** — extracts patient demographics, vitals, labs, medications, diagnoses, procedures, allergies
+- **Source-grounded** — every extracted value traces to the input document
+- **No patient identifiers** — extracts age/sex only, strips names/MRN/DOB
+- **On-prem deployable** — 3B parameters, runs on CPU via GGUF quantization
+- **98% JSON validity** on held-out gold set
+
+## Training
+
+| Parameter | Value |
+|-----------|-------|
+| Base model | Qwen/Qwen2.5-3B-Instruct |
+| Method | QLoRA (4-bit, r=16, alpha=32) |
+| Training data | 3,438 examples (126 curated + 3,312 Synthea-rendered) |
+| Epochs | 2 |
+| Final loss | 0.14 |
+| GPU | Kaggle T4 (free tier) |
+| Training time | ~2h 40m |
+
+## Evaluation (50 held-out gold examples)
+
+| Metric | Value |
+|--------|-------|
+| JSON validity | 98% |
+| Training loss | 1.23 → 0.14 |
+
+## Usage
+
+```python
+from peft import AutoPeftModelForCausalLM
+from transformers import AutoTokenizer
+
+model = AutoPeftModelForCausalLM.from_pretrained("shekharp77/Mira-1")
+tokenizer = AutoTokenizer.from_pretrained("shekharp77/Mira-1")
+
+messages = [
+    {"role": "system", "content": "You are a clinical information extraction system..."},
+    {"role": "user", "content": "Patient: 45/M\nHb 12.5 g/dL (13-17) LOW\nWBC 8.2 x10^9/L (4-11) Normal"},
+]
+
+inputs = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True)
+outputs = model.generate(inputs, max_new_tokens=2048, temperature=0)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Schema
+
+Outputs conform to this schema (10 required top-level fields):
+- `document_type`: lab_report | medication_list | discharge_summary | pathology_report | intake_form | progress_note | other
+- `patient`: {age, sex}
+- `encounter`: {date, department}
+- `vitals[]`, `labs[]`, `medications[]`, `diagnoses[]`, `procedures[]`, `allergies[]`
+- `extraction_notes`
+
+## Limitations
+
+- English only (v0)
+- Trained on synthetic data (Synthea + curated seeds), not real clinical records
+- Every output is a **draft for human review** — not for autonomous clinical decisions
+- No ICD-10/SNOMED coding unless explicitly in the source document
+
+## License
+
+Apache-2.0 (same as base model)

adapter_config.json

@@ -0,0 +1,50 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "Qwen2ForCausalLM",
+    "parent_library": "transformers.models.qwen2.modeling_qwen2",
+    "unsloth_fixed": true
+  },
+  "base_model_name_or_path": "unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.1",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "o_proj",
+    "v_proj",
+    "gate_proj",
+    "q_proj",
+    "up_proj",
+    "down_proj",
+    "k_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:15fb422beab5e8cdd789c95dadae49c32973f1cc68be23bf58fc4a1d0e3ee2a9
+size 119801528

chat_template.jinja

@@ -0,0 +1,54 @@
+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
+    {%- endif %}
+    {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
+    {%- else %}
+        {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

tokenizer.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:bd5948af71b4f56cf697f7580814c7ce8b80595ef985544efcacf716126a2e31
+size 11422356

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "is_local": false,
+  "model_max_length": 32768,
+  "pad_token": "<|PAD_TOKEN|>",
+  "padding_side": "left",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null,
+  "added_tokens_decoder": {
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+    }
+  }
+}