Update README.md

README.md

@@ -17,6 +17,118 @@ language:
 - **License:** apache-2.0
 - **Finetuned from model :** unsloth/phi-4-unsloth-bnb-4bit
 
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+# Fine-tuned Phi-4 Model Documentation
+
+## 📌 Introduction
+This documentation provides an in-depth overview of the **fine-tuned Phi-4 conversational AI model**, detailing its **training methodology, parameters, dataset, model deployment, and usage instructions**.
+
+## 🔹 Model Overview
+**Phi-4** is a transformer-based language model optimized for **natural language understanding and text generation**. We have fine-tuned it using **LoRA (Low-Rank Adaptation)** with the **Unsloth framework**, making it lightweight and efficient while preserving the base model's capabilities.
+
+## 🔹 Training Details
+### **🛠 Fine-tuning Methodology**
+We employed **LoRA (Low-Rank Adaptation)** for fine-tuning, which significantly reduces the number of trainable parameters while retaining the model’s expressive power.
+
+### **📑 Dataset Used**
+- **Dataset Name**: `mlabonne/FineTome-100k`
+- **Dataset Size**: 100,000 examples
+- **Data Format**: Conversational AI dataset with structured prompts and responses.
+- **Preprocessing**: The dataset was standardized using `unsloth.chat_templates.standardize_sharegpt()`
+
+### **🔢 Training Parameters**
+| Parameter             | Value |
+|----------------------|-------|
+| LoRA Rank (`r`)     | 16    |
+| LoRA Alpha          | 16    |
+| LoRA Dropout        | 0     |
+| Target Modules      | `q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj` |
+| Max Sequence Length | 2048  |
+| Load in 4-bit       | True  |
+| Gradient Checkpointing | `unsloth` |
+| Fine-tuning Duration | **10 epochs** |
+| Optimizer Used      | AdamW |
+| Learning Rate       | 2e-5  |
+
+## 🔹 How to Load the Model
+To load the fine-tuned model, use the **Unsloth framework**:
+
+```python
+from unsloth import FastLanguageModel
+from unsloth.chat_templates import get_chat_template
+from peft import PeftModel
+
+model_name = "unsloth/Phi-4"
+max_seq_length = 2048
+load_in_4bit = True
+
+# Load model and tokenizer
+model, tokenizer = FastLanguageModel.from_pretrained(
+    model_name=model_name,
+    max_seq_length=max_seq_length,
+    load_in_4bit=load_in_4bit
+)
+
+# Apply LoRA adapter
+model = FastLanguageModel.get_peft_model(
+    model,
+    r=16,
+    target_modules=["q_proj", "k_proj", "v_proj", "o_proj",
+                    "gate_proj", "up_proj", "down_proj"],
+    lora_alpha=16,
+    lora_dropout=0,
+    bias="none",
+    use_gradient_checkpointing="unsloth"
+)
+```
+
+## 🔹 Deploying the Model
+### **🚀 Using Google Colab**
+1. Install dependencies:
+    ```bash
+    pip install gradio transformers torch unsloth peft
+    ```
+2. Load the model using the script above.
+3. Run inference using the chatbot interface.
+
+### **🚀 Deploy on Hugging Face Spaces**
+1. Save the script as `app.py`.
+2. Create a `requirements.txt` file with:
+    ```
+    gradio
+    transformers
+    torch
+    unsloth
+    peft
+    ```
+3. Upload the files to a new **Hugging Face Space**.
+4. Select **Python environment** and click **Deploy**.
+
+## 🔹 Using the Model
+### **🗨 Chatbot Interface (Gradio UI)**
+To interact with the fine-tuned model using **Gradio**, use:
+
+```python
+import gradio as gr
+
+def chat_with_model(user_input):
+    inputs = tokenizer(user_input, return_tensors="pt")
+    output = model.generate(**inputs, max_length=200)
+    response = tokenizer.decode(output[0], skip_special_tokens=True)
+    return response
+
+demo = gr.Interface(
+    fn=chat_with_model,
+    inputs=gr.Textbox(label="Your Message"),
+    outputs=gr.Textbox(label="Chatbot's Response"),
+    title="LoRA-Enhanced Phi-4 Chatbot"
+)
+
+demo.launch()
+```
+
+## 📌 Conclusion
+This **fine-tuned Phi-4 model** delivers **optimized conversational AI capabilities** using **LoRA fine-tuning and Unsloth’s 4-bit quantization**. The model is **lightweight, memory-efficient**, and suitable for chatbot applications in both **research and production environments**.
+
+
 
 [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)