Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+datasets:
+- SohamGhadge/casual-conversation
+language:
+- en
+base_model:
+- openai-community/gpt2-medium
+pipeline_tag: question-answering
+tags:
+- transformers
+- peft
+- gpt2
+---
+
+## 🧠 Fine-Tuned GPT-2 Medium for Conversational AI
+This project fine-tunes the `gpt2-medium` language model to support natural, casual **conversational dialogue** using **PEFT + LoRA**.
+---
+### 🚀 Model Summary
+* **Base model**: `gpt2-medium`
+* **Objective**: Enable natural question-answering and dialogue
+* **Training method**: Supervised Fine-Tuning (SFT) using PEFT with LoRA adapters
+* **Tokenizer**: `gpt2` (same as base model)
+---
+### 📈 Training Metrics
+| Metric              | Value          |
+| ------------------- | -------------- |
+| Global Steps        | 2611           |
+| Final Training Loss | 2.185          |
+| Training Runtime    | 430.61 seconds |
+| Samples/sec         | 138.41         |
+| Steps/sec           | 17.32          |
+| Total FLOPs         | 1.12 × 10¹⁵    |
+| Epochs              | 7.0            |
+> These metrics reflect final performance after complete training.
+---
+### 💬 Inference Script
+Chat with the model using the `talk()` function below:
+```python
+def talk(model=peft_model, tokenizer=tokenizer, device=device):
+    print("Start chatting with the bot! Type 'exit' to stop.\n")
+    while True:
+        question = input("You: ")
+        if question.lower() == "exit":
+            print("Goodbye!")
+            break
+
+        prompt = f"User: {question}\nBot:"
+        inputs = tokenizer(prompt, return_tensors="pt").to(device)
+
+        with torch.no_grad():
+            outputs = model.generate(
+                **inputs,
+                max_new_tokens=20,
+                do_sample=True,
+                temperature=0.7,
+                top_p=0.9,
+                pad_token_id=tokenizer.eos_token_id
+            )
+
+        response = tokenizer.decode(
+            outputs[0][inputs["input_ids"].shape[-1]:],
+            skip_special_tokens=True
+        )
+
+        # Clean response
+        response = response.split(".")
+        response = ".".join(response[:-1]) + "."
+        print("Bot:", response.strip())
+```
+
+* 🤖 **Stateless**: No memory across turns (yet).
+* 🌱 **Future idea**: Add memory/context for multi-turn dialogue.
+---
+### ⚙️ Quick Setup
+To use this model locally:
+```bash
+pip install transformers peft accelerate
+```