Update README.md

README.md

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+# 🤖 Qwen Alpaca GGUF
+
+A fine tuned **Qwen2.5-0.5B-Instruct** language model trained on the **tatsu-lab/alpaca** instruction dataset. The model was fine tuned using **Unsloth**, quantized to **GGUF (Q4_K_M)**, and can be run locally with **Ollama** or **llama.cpp**.
+
+---
+
+## 🚀 Model Details
+
+| Property | Value |
+|----------|-------|
+| Base Model | Qwen2.5-0.5B-Instruct |
+| Fine Tuning | LoRA |
+| Framework | Unsloth |
+| Dataset | tatsu-lab/alpaca |
+| Format | GGUF |
+| Quantization | Q4_K_M |
+| Inference | Ollama, llama.cpp |
+| Language | English |
+
+---
+
+## ✨ Features
+
+- Instruction following chatbot
+- Lightweight 0.5B parameter model
+- GGUF format for efficient CPU inference
+- Optimized using Q4_K_M quantization
+- Compatible with Ollama
+- Compatible with llama.cpp
+- Easy local deployment
+
+---
+
+## 📦 Model File
+
+```
+Qwen2.5-0.5B-Instruct.Q4_K_M.gguf
+```
+
+---
+
+# 🛠 Fine Tuning Pipeline
+
+```
+Base Model
+        │
+        ▼
+Qwen2.5-0.5B-Instruct
+        │
+        ▼
+Alpaca Instruction Dataset
+        │
+        ▼
+LoRA Fine Tuning
+        │
+        ▼
+Unsloth
+        │
+        ▼
+Merge LoRA Adapters
+        │
+        ▼
+GGUF Conversion
+        │
+        ▼
+Q4_K_M Quantization
+        │
+        ▼
+Inference using Ollama / llama.cpp
+```
+
+---
+
+# 📚 Dataset
+
+This model was fine tuned using the **tatsu-lab/alpaca** instruction dataset.
+
+The dataset contains thousands of instruction and response pairs designed to improve instruction following ability.
+
+---
+
+# ⚡ Run with Ollama
+
+Create a Modelfile
+
+```text
+FROM ./Qwen2.5-0.5B-Instruct.Q4_K_M.gguf
+```
+
+Create the model
+
+```bash
+ollama create fineqwen -f Modelfile
+```
+
+Run the model
+
+```bash
+ollama run fineqwen
+```
+
+---
+
+# 🖥 Example Terminal
+
+```text
+$ ollama create fineqwen -f Modelfile
+
+transferring model...
+creating new layer...
+writing manifest...
+success
+
+$ ollama run fineqwen
+
+>>> Explain Transformers in simple words.
+
+Transformers are neural networks designed to process sequences using
+self-attention, allowing them to understand relationships between words
+efficiently.
+```
+
+---
+
+# 🦙 Run using llama.cpp
+
+```bash
+llama-cli \
+-hf ciphermosaic/qwen-alpaca-gguf \
+--jinja
+```
+
+or
+
+```bash
+llama-cli \
+-m Qwen2.5-0.5B-Instruct.Q4_K_M.gguf
+```
+
 ---
-title: ByteBot
-emoji: 💬
-colorFrom: yellow
-colorTo: purple
-sdk: gradio
-sdk_version: 6.5.1
-app_file: app.py
-pinned: false
-hf_oauth: true
-hf_oauth_scopes:
-- inference-api
+
+# 🌐 Hugging Face Space
+
+Interactive chatbot available on Hugging Face Spaces.
+
+---
+
+# 📊 Quantization
+
+This model uses
+
+```
+Q4_K_M
+```
+
+Benefits
+
+- Smaller model size
+- Faster inference
+- Lower RAM usage
+- Minimal quality loss
+
+---
+
+# 🧰 Tech Stack
+
+- Python
+- Hugging Face Transformers
+- Unsloth
+- PEFT (LoRA)
+- GGUF
+- llama.cpp
+- Ollama
+- Hugging Face Hub
+- Gradio
+
+---
+
+# 📁 Repository Structure
+
+```
+.
+├── Modelfile
+├── Qwen2.5-0.5B-Instruct.Q4_K_M.gguf
+├── README.md
+├── config.json
+```
+
+---
+
+# 👨‍💻 Author
+
+**CipherMosaic**
+
+GitHub: https://github.com/CipherMosaic
+
+Hugging Face: https://huggingface.co/ciphermosaic
+
 ---
 
-An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index).
+## ⭐ If you found this project useful, consider giving it a star!