Update README.md

README.md

@@ -1,21 +1,113 @@
 ---
-base_model: unsloth/llama-3.2-1b-instruct-unsloth-bnb-4bit
+base_model: meta-llama/Llama-3.2-1B-Instruct
 tags:
 - text-generation-inference
 - transformers
 - unsloth
 - llama
+- gguf
+- chain-of-thought
 license: apache-2.0
 language:
 - en
 ---
 
-# Uploaded finetuned  model
+<div align="center">
+<img src="https://cdn-uploads.huggingface.co/production/uploads/669777597cb32718c20d97e9/4emWK_PB-RrifIbrCUjE8.png"
+     alt="Title card" 
+     style="width: 500px;
+            height: auto;
+            object-position: center top;">
+</div>
 
-- **Developed by:** alphaaico
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/llama-3.2-1b-instruct-unsloth-bnb-4bit
+**Website - https://www.alphaai.biz**
 
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+# Model Name: Medical-Guide-COT-llama3.2-1B
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+**Developed by:** Alpha AI
+**License:** apache-2.0
+**Finetuned from model:** meta-llama/Llama-3.2-1B-Instruct
+**Formats available:** Float16 (safetensors + GGUF-f16), GGUF quantized (q4\_k\_m, q5\_k\_m, q8\_0)
+
+## Overview
+
+**Medical-Guide-COT-llama3.2-1B** is a lightweight yet powerful medical reasoning model designed to produce explicit **Chain of Thought (CoT)** reasoning with `<think>...</think>` tags for transparency and clarity. Built for interpretability and performance, this model excels in structured medical question answering.
+
+* **Finetuning Objective:** Supervised fine-tuning (SFT) on medical QA datasets with enforced reasoning chains.
+* **Instruction format:** Adheres to Llama 3.2 Instruct prompting standards.
+* **Deployment flexibility:** Offers multiple GGUF quantized variants for local, edge, or efficient inference environments.
+
+## Training Data
+
+* **Public sources:** PubMedQA, MedMCQA, USMLE-type questions (filtered)
+* **Proprietary augmentation:** Alpha AI's curated "Clinical-Cases-CoT" dataset with physician-authored reasoning chains
+* **Sample size:** 42,000 examples (approx. 60% public / 40% private)
+* **Token structure:**
+
+  ```
+  <think>
+  Step-by-step clinical reasoning...
+  </think>
+  Final answer.
+  ```
+
+## Model Specifications
+
+| Attribute      | Value                                     |
+| -------------- | ----------------------------------------- |
+| Base Model     | meta-llama/Llama-3.2-1B-Instruct          |
+| Model Type     | Causal Language Model                     |
+| Finetuned By   | Alpha AI                                  |
+| Precision      | Float16, GGUF q4\_k\_m / q5\_k\_m / q8\_0 |
+| Context Length | 8,192 tokens                              |
+| Language       | English                                   |
+
+## Intended Use
+
+* **Medical Education:** Transparent QA for students (USMLE/PLAB prep)
+* **Prototype Decision Support:** Clear reasoning steps before answers
+* **Research on COT Safety:** Evaluation of model interpretability and hallucination control
+
+## Example Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "alpha-ai/Medical-Guide-COT-llama3.2-1B"
+model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+
+prompt = """### Question:
+A 65-year-old male presents with sudden chest pain radiating to the back. Most likely diagnosis?
+### Answer:
+"""
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.7, top_p=0.9)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+**Expected Output Format:**
+
+```text
+<think>
+Sudden tearing chest pain suggests aortic dissection.
+Hypertension is a key risk factor. Location of pain supports Stanford Type A.
+</think>
+Acute aortic dissection (Stanford Type A)
+```
+
+## Limitations & Usage Warnings
+
+* **Not a clinical diagnostic tool.** Use only for research or educational purposes.
+* **Bias & Hallucination Risk.** Outputs must be validated by qualified professionals.
+* **Sensitive Content.** Model not trained on PHI but care should be taken with input prompts.
+
+## License
+
+Distributed under the **Apache-2.0** license.
+
+## Acknowledgments
+
+Thanks to Meta AI for Llama-3.2, the creators of open medical QA datasets, and the Alpha AI medical advisory board for domain alignment and data verification.
+
+**Website:** [https://www.alphaai.biz](https://www.alphaai.biz)