Update README.md

README.md

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----
-license: gemma
----
+---
+license: gemma
+---
+# Gemma-2-9B-CPT-SahabatAI-Instruct GGUF
+
+This is a GGUF quantized version of Gemma 2 9B, fine-tuned with custom instructions by SahabatAI and optimized for CPU inference using Q4_K_M quantization.
+
+## Model Details
+
+- **Base Model**: Gemma 2 9B
+- **Instruction Format**: SahabatAI Instruct v1
+- **Quantization**: GGUF Q4_K_M (4-bit with Medium precision for Key/Value cache)
+- **Original Size**: 9B parameters
+- **Quantized Size**: ~5GB
+- **Context Length**: 8192 tokens
+- **License**: Gemma Terms of Use
+
+## Description
+
+This model is a quantized version of Gemma 2 9B, fine-tuned with custom instruction format by SahabatAI. The Q4_K_M quantization provides a good balance between model size, speed, and quality. The instruction format is optimized for general-purpose tasks while maintaining model coherence and reliability.
+
+## Usage
+
+### oobabooga's text-generation-webui Setup
+
+1. **Install text-generation-webui**:
+```bash
+git clone https://github.com/oobabooga/text-generation-webui
+cd text-generation-webui
+pip install -r requirements.txt
+```
+
+2. **Download Model**:
+```bash
+mkdir models
+cd models
+# Download gemma2-9B-cpt-sahabatai-instruct-v1-Q4_K_M.gguf from Hugging Face
+```
+
+3. **Launch the Web UI**:
+```bash
+python server.py --model gemma2-9B-cpt-sahabatai-instruct-v1-Q4_K_M.gguf
+```
+
+### Recommended Launch Parameters
+
+For optimal performance on different hardware:
+
+**CPU Only**:
+```bash
+python server.py --model gemma2-9B-cpt-sahabatai-instruct-v1-Q4_K_M.gguf --cpu --n_ctx 8192
+```
+
+**GPU (CUDA)**:
+```bash
+python server.py --model gemma2-9B-cpt-sahabatai-instruct-v1-Q4_K_M.gguf --n_ctx 8192 --gpu-memory 6
+```
+
+### Recommended Generation Parameters
+
+```yaml
+temperature: 0.7
+top_p: 0.9
+top_k: 40
+repetition_penalty: 1.1
+max_new_tokens: 2048
+```
+
+### Instruction Format
+
+The model responds best to this instruction format:
+```
+<|system|>You are a helpful AI assistant.</|system|>
+
+<|user|>Your question here</|user|>
+
+<|assistant|>
+```
+
+## Performance Benchmarks
+
+| Device                 | Tokens/sec | Memory Usage |
+|-----------------------|------------|--------------|
+| CPU (8 cores)         | ~15 t/s    | 6GB         |
+| NVIDIA RTX 3060 (6GB) | ~40 t/s    | 5GB         |
+| NVIDIA RTX 4090       | ~100 t/s   | 5GB         |
+
+## Example Outputs
+
+```
+<|system|>You are a helpful AI assistant.</|system|>
+
+<|user|>What is the capital of Indonesia?</|user|>
+
+<|assistant|>Jakarta is the capital city of Indonesia. It is located on the northwestern coast of Java, the most populous island in Indonesia. Jakarta serves as the country's economic, cultural, and political center.
+
+<|user|>Write a simple Python function to calculate factorial.</|user|>
+
+<|assistant|>Here's a simple recursive function to calculate factorial:
+
+def factorial(n):
+    if n == 0 or n == 1:
+        return 1
+    return n * factorial(n-1)
+```
+
+## Known Limitations
+
+- Requires minimum 6GB RAM for CPU inference
+- Best performance with GPU having 6GB+ VRAM
+- May show degraded performance on very long contexts (>4096 tokens)
+- Quantization may impact some mathematical and logical reasoning tasks
+
+## Fine-tuning Details
+
+- Base Model: Gemma 2 9B
+- Instruction Format: Custom SahabatAI format
+- Quantization: Q4_K_M using llama.cpp
+
+## License
+
+This model is subject to the Gemma Terms of Use. Please refer to Google's Gemma licensing terms for commercial usage.
+
+## Acknowledgments
+
+- Google for the Gemma 2 base model
+- SahabatAI for instruction fine-tuning
+- TheBloke for GGUF conversion tools
+- oobabooga for text-generation-webui
+
+## Support
+
+For issues and questions:
+- Open an issue in this repository
+- Visit our Discord: [Your Discord Link]
+- Email: [Your Support Email]
+
+## Updates & Versions
+
+- v1.0 (2024-03): Initial release with Q4_K_M quantization
+- Future updates will be listed here