Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+language:
+- en
+tags:
+- mental-health
+- text-generation
+- conversational-ai
+- gpt2
+pipeline_tag: text-generation
+base_model: openai-community/gpt2
+
+# GPT-2 (Fine-Tuned for MindPadi)
+
+This is a fine-tuned version of GPT-2 for the **MindPadi** mental health chatbot. It has been adapted to generate empathetic, therapeutic, and contextually relevant responses for mental health support. It is the primary generative model used in long-form conversation and therapy-related dialogue management in MindPadi.
+
+
+
+## 🧠 Model Summary
+
+- **Model Type:** GPT-2 (12-layer transformer)
+- **Parameters:** ~124M
+- **Fine-Tuned For:** Empathetic and supportive text generation
+- **Used In:** `app/chatbot/fusion_bot.py`
+- **Architecture:** Decoder-only transformer (causal LM)
+- **Framework:** Hugging Face Transformers + PyTorch
+
+
+
+## 🧾 Intended Use
+
+### ✔️ Primary Use Cases
+- Generating thoughtful, compassionate responses in mental health conversations
+- Completing sentences in a therapy dialogue setting
+- Supporting GPTFusion workflows in MindPadi backend
+
+### 🚫 Not Recommended For
+- Clinical diagnoses or medical decisions
+- Domains outside mental health (e.g., finance, legal)
+- Multilingual generation (trained on English only)
+
+
+
+## 🏋️‍♀️ Training Details
+
+- **Base Model:** `gpt2` from Hugging Face
+- **Fine-Tuning Script:** `training/finetune_gpt2_pipeline.py`
+- **Datasets:** Mental health dialogue datasets (e.g., therapy transcripts, Reddit mental health subreddits)
+  - Location: `training/datasets/finetuned/`
+- **Preprocessing:**
+  - Cleaned for profanity, PII, and formatting noise
+  - Converted to conversation format: `User: ... Assistant: ...`
+
+### Hyperparameters
+- Epochs: 3–5
+- Batch Size: 4–8
+- Learning Rate: 5e-5
+- Warmup Steps: 200
+- Optimizer: AdamW
+
+### Hardware
+- NVIDIA RTX 2080 / A100 / equivalent (local or cloud)
+
+
+
+## 📈 Evaluation
+
+- **Evaluation Script:** `training/evaluate_model.py`
+- **Metrics:**
+  - Perplexity: Reduced ~20% compared to base GPT-2
+  - BLEU Score: Improved ~12% in test responses
+  - Human Evaluation: Higher relevance and emotional alignment in blind tests
+- **Examples:** Available in `logs/training.log` and test dialogues
+
+
+
+## 📂 Files
+
+| File | Purpose |
+|------|---------|
+| `config.json` | Model architecture |
+| `pytorch_model.bin` or `model.safetensors` | Fine-tuned weights |
+| `tokenizer.json`, `vocab.json`, `merges.txt` | Tokenizer and BPE merge rules |
+| `checkpoint-*/` | Intermediate training checkpoints (optional) |
+
+
+
+## 💬 Example Usage
+
+```python
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+
+model = GPT2LMHeadModel.from_pretrained("mindpadi/gpt2")
+tokenizer = GPT2Tokenizer.from_pretrained("mindpadi/gpt2")
+
+prompt = "User: I feel hopeless and tired.\nAssistant:"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_length=100, do_sample=True)
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+````
+
+
+
+## 🔧 Integration in MindPadi
+
+This model is integrated into:
+
+* `app/chatbot/fusion_bot.py`: Primary text generator
+* `app/chatbot/gpt_router.py`: Fusion routing between GPT-2 and DistilGPT2
+* `app/chatbot/core.py`: Chat interface logic
+* LangGraph workflows: Via GPTFusionRouter nodes
+
+
+
+## ⚠️ Limitations
+
+* **Bias:** May carry biases from internet pretraining or mental health corpora
+* **Language:** English-only
+* **Token Limit:** \~1024 tokens context window
+* **Sensitivity:** May generate inappropriate responses if inputs are adversarial or out-of-distribution
+* **Non-Determinism:** Sampling may produce varied outputs even for the same input
+
+
+
+## 🔐 Ethical Considerations
+
+* Not intended for crisis response or as a substitute for professional help
+* Includes guardrails to detect emergency keywords (e.g., "suicide", "abuse")
+* Should always inform users they are interacting with AI (see `chat_interface.py`)
+* Responses are not clinically validated; user discretion advised
+
+
+
+## 🧪 Deployment
+
+You can deploy this model via Hugging Face Inference Endpoints for GPU-powered responses.
+
+```python
+import requests
+
+api_url = "https://<your-endpoint>.hf.space"
+headers = {"Authorization": f"Bearer <your-token>", "Content-Type": "application/json"}
+
+payload = {"inputs": "User: I feel anxious.\nAssistant:"}
+response = requests.post(api_url, headers=headers, json=payload)
+print(response.json())
+```
+
+
+
+## 📜 License
+
+MIT License – Free for commercial and non-commercial use with attribution.
+
+
+
+## 📬 Contact
+
+* **Project:** [MindPadi AI Chatbot](https://huggingface.co/mindpadi)
+* **Maintainer:** MindPadi Team
+* **Email:** \[[you@example.com](mailto:you@example.com)]
+* **GitHub:** \[github.com/mindpadi/mindpadi]
+
+*Last updated: May 2025*