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README.md

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+
+---
+title: Pharma Assistant v3
+tags:
+- medical
+- healthcare
+- chatbot
+- RAG
+- fine-tuning
+- unsloth
+- tinyllama
+---
+
+# Pharma Assistant v3
+
+This model is a fine-tuned version of `unsloth/tinyllama-bnb-4bit` for pharmaceutical question answering, developed using a 3-stage fine-tuning pipeline with Unsloth.
+
+## Training Pipeline
+
+The model was trained using the following stages:
+1.  **Stage 1: Non-instruction continued pretraining** on PDF documents related to Metformin and Lipid Therapy knowledge.
+2.  **Stage 2: Instruction fine-tuning** on a custom `pharma_instruction_dataset.jsonl`.
+3.  **Stage 3: DPO (Direct Preference Optimization)** using a `pharma_preference_dataset.jsonl` to align with preferred responses.
+
+## Model Details
+
+- **Base Model**: `unsloth/tinyllama-bnb-4bit`
+- **Fine-tuning Framework**: Unsloth
+- **Architecture**: Llama-based, 4-bit quantized
+
+## Usage
+
+To use this model for inference, you can load it using the Hugging Face Transformers library and Unsloth:
+
+```python
+from unsloth import FastLanguageModel
+import torch
+
+# Load model
+model, tokenizer = FastLanguageModel.from_pretrained(
+    model_name = "ragpalgit/pharma-assistant-v3", # YOUR MODEL_ID
+    max_seq_length = 512,
+    dtype = None,
+    load_in_4bit = True,
+)
+
+# Example inference (using generate_answer helper from notebook)
+instruction = "Explain metformin in simple language."
+prompt = f"### Instruction:
+{instruction}
+
+### Response:
+"
+
+inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
+
+with torch.inference_mode():
+    output = model.generate(
+        **inputs,
+        max_new_tokens=150,
+        do_sample=True,
+        temperature=0.7,
+        top_p=0.9,
+        repetition_penalty=1.1,
+        pad_token_id=tokenizer.eos_token_id,
+        eos_token_id=tokenizer.eos_token_id,
+    )
+
+input_tokens = inputs["input_ids"].shape[-1]
+generated_tokens = output[0][input_tokens:]
+print(tokenizer.decode(generated_tokens, skip_special_tokens=True).strip())
+```