Update README.md

README.md

@@ -1,162 +1,65 @@
 ---
+language: en
+license: apache-2.0
+library_name: transformers
 tags:
-- llama
-- llama-3
-- vllm
-- causal-lm
-- cognitive-therapy
-- mental-health
-- conversational
-- peft
-- lora
-license: mit
-datasets:
-- Lumiiree/therapod-dpo
-inference: true
+  - llama
+  - causal-lm
+  - merged
+  - vllm
+inference:
+  parameters:
+    max_new_tokens: 256
+    temperature: 0.7
+    top_p: 0.9
+    repetition_penalty: 1.1
 ---
 
-# 🧠 CBT-Copilot: LLaMA 3.2B Fine-Tuned for Cognitive Therapy
+# CBT-Copilot 🧠
 
-Welcome to **CBT-Copilot**, an open-source LLM fine-tuned on therapy-aligned dialogues using the [Lumiiree/therapod-dpo](https://huggingface.co/datasets/Lumiiree/therapod-dpo) dataset. This model is designed to act as a **compassionate and supportive AI assistant**, trained in the tone of cognitive behavioral therapy (CBT), and suitable for mental health support applications.
+CBT-Copilot is a fine-tuned version of `meta-llama/Llama-3.2-3B-Instruct`, designed to simulate conversations for cognitive behavioral therapy (CBT) support. It has been trained using LoRA and merged into a standalone model.
 
----
-
-## 🔧 Model Details
-
-- **Base Model**: [`meta-llama/Llama-3.2-3B-Instruct`](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct)
-- **Fine-Tuning Method**: LoRA (Low-Rank Adaptation)
-- **Dataset**: [`Lumiiree/therapod-dpo`](https://huggingface.co/datasets/Lumiiree/therapod-dpo)
-- **Use Case**: Empathetic responses, journaling prompts, CBT-style thought reframing
-- **Trained by**: [Thillai Chithambaram](https://huggingface.co/thillaic)
-
----
-
-## 🧠 Intended Use
-
-This model can be integrated into:
-
-- 💬 **Mental health chatbots**
-- 📔 **Journaling apps with AI reflections**
-- 🧘 **Self-help tools for cognitive restructuring**
-- 🧑‍⚕️ **Therapist assistants (non-clinical use)**
-
-> ⚠️ **Disclaimer**: This model is not a replacement for licensed mental health professionals. It should be used only as an assistant or for research.
-
----
+The model is now compatible with `transformers`, `vLLM`, and other inference frameworks.
 
-## 🏗️ Training Configuration
-
-### ✅ LoRA Settings
-```python
-peft_config = LoraConfig(
-    r=8,
-    lora_alpha=16,
-    target_modules=["q_proj", "v_proj"],
-    lora_dropout=0.05,
-    bias="none",
-    task_type="CAUSAL_LM",
-)
-```
-
-### ✅ TrainingArguments
-```python
-args = TrainingArguments(
-    output_dir="llama-cbt-checkpoints",
-    per_device_train_batch_size=1,
-    gradient_accumulation_steps=4,
-    learning_rate=2e-5,
-    num_train_epochs=1,
-    logging_steps=100,
-    save_strategy="epoch",
-    bf16=True,
-    optim="paged_adamw_8bit",
-)
-```
-
-> Training was performed using Hugging Face's `transformers` + `peft` libraries with LoRA applied to key attention modules for lightweight adaptation.
-
----
+## 🚀 How to Use (vLLM)
 
-## 🚀 How to Use
-
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
-
-model_id = "thillaic/CBT-Copilot"
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = AutoModelForCausalLM.from_pretrained(model_id)
-
-pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
-
-prompt = "I feel overwhelmed and stuck lately. What should I do?"
-response = pipe(prompt, max_new_tokens=200, do_sample=True, temperature=0.7)
-
-print(response[0]['generated_text'])
-```
-
----
-
-## 💡 Example Prompts
-
-- "I often feel like I’m not good enough. Help me reframe this thought."
-- "Give me a CBT-style journaling prompt for today."
-- "How can I deal with negative self-talk?"
-
----
-
-## ⚡ Inference with vLLM
-
-This model is **compatible with [vLLM](https://github.com/vllm-project/vllm)** — a fast and memory-efficient inference engine for LLMs.
-
-### 🚀 Quick Start with vLLM
+You can serve it with [vLLM](https://github.com/vllm-project/vllm):
 
 ```bash
-pip install "vllm[serve]"
-
-python -m vllm.entrypoints.api_server \
-    --model thillaic/CBT-Copilot
+python3 -m vllm.entrypoints.openai.api_server --model your-username/CBT-Copilot
 ```
 
-### OpenAI-Compatible API Example
+Then query it like this:
 
 ```python
 import openai
 
+openai.api_key = "EMPTY"
 openai.api_base = "http://localhost:8000/v1"
-openai.api_key = "EMPTY"  # not needed for local use
 
 response = openai.ChatCompletion.create(
-    model="thillaic/CBT-Copilot",
+    model="CBT-Copilot",
     messages=[
-        {"role": "system", "content": "You are a compassionate CBT therapist."},
-        {"role": "user", "content": "I'm feeling anxious lately. What should I do?"}
+        {"role": "user", "content": "I've been feeling really anxious lately. What can I do?"}
     ]
 )
 
-print(response.choices[0].message["content"])
+print(response["choices"][0]["message"]["content"])
 ```
 
----
+## 🧠 Intended Use
 
-## 🧾 License
+This model is intended for educational and prototyping purposes in mental health-related chatbot systems. It is **not a substitute for professional therapy**.
 
-This project is open-sourced for educational and research purposes under the **MIT License**.
+## 📜 License
 
----
+This model is licensed under the Apache 2.0 license.
 
-## 🙏 Acknowledgements
-
-- Fine-tuned on the excellent [`therapod-dpo`](https://huggingface.co/datasets/Lumiiree/therapod-dpo) dataset
-- Built using Meta’s LLaMA 3.2B base model
-- LoRA integration powered by Hugging Face PEFT
 
 ---
 
-## 🔗 Links
-
-- 🤗 Model: [huggingface.co/thillaic/CBT-Copilot](https://huggingface.co/thillaic/CBT-Copilot)
-- 📓 Dataset: [Lumiiree/therapod-dpo](https://huggingface.co/datasets/Lumiiree/therapod-dpo)
+*Model prepared and fine-tuned by **Thillai Chithambaram***
 
 ---
 
-*Crafted with care by Thillai Chithambaram for the future of compassionate AI.*
+**Made by ThillaiC**