Instructions to use muhammadmuneeb007/BioStarsGPT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use muhammadmuneeb007/BioStarsGPT with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="muhammadmuneeb007/BioStarsGPT", filename="qwen-model-f16.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use muhammadmuneeb007/BioStarsGPT with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf muhammadmuneeb007/BioStarsGPT:F16 # Run inference directly in the terminal: llama-cli -hf muhammadmuneeb007/BioStarsGPT:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf muhammadmuneeb007/BioStarsGPT:F16 # Run inference directly in the terminal: llama-cli -hf muhammadmuneeb007/BioStarsGPT:F16
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf muhammadmuneeb007/BioStarsGPT:F16 # Run inference directly in the terminal: ./llama-cli -hf muhammadmuneeb007/BioStarsGPT:F16
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf muhammadmuneeb007/BioStarsGPT:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf muhammadmuneeb007/BioStarsGPT:F16
Use Docker
docker model run hf.co/muhammadmuneeb007/BioStarsGPT:F16
- LM Studio
- Jan
- Ollama
How to use muhammadmuneeb007/BioStarsGPT with Ollama:
ollama run hf.co/muhammadmuneeb007/BioStarsGPT:F16
- Unsloth Studio
How to use muhammadmuneeb007/BioStarsGPT with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for muhammadmuneeb007/BioStarsGPT to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for muhammadmuneeb007/BioStarsGPT to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for muhammadmuneeb007/BioStarsGPT to start chatting
- Docker Model Runner
How to use muhammadmuneeb007/BioStarsGPT with Docker Model Runner:
docker model run hf.co/muhammadmuneeb007/BioStarsGPT:F16
- Lemonade
How to use muhammadmuneeb007/BioStarsGPT with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull muhammadmuneeb007/BioStarsGPT:F16
Run and chat with the model
lemonade run user.BioStarsGPT-F16
List all available models
lemonade list
| FROM ./qwen-model-f16.gguf | |
| TEMPLATE """<|im_start|>system | |
| {{ .System }}<|im_end|> | |
| <|im_start|>user | |
| {{ .Prompt }}<|im_end|> | |
| <|im_start|>assistant | |
| """ | |
| SYSTEM """You are Qwen, created by Alibaba Cloud. You are a helpful AI assistant specialized in polygenic risk score (PRS) analysis and related genomic tools. You provide clear, accurate, and practical information about: | |
| - Calculating and interpreting polygenic risk scores | |
| - Using PRS tools like PRSice-2, PLINK, and LDpred | |
| - Understanding GWAS summary statistics and their application | |
| - Quality control procedures for genetic data | |
| - Population structure and ancestry considerations in PRS | |
| - Cross-ancestry portability of polygenic scores | |
| - Best practices for PRS validation and evaluation | |
| - Interpreting PRS results in clinical and research contexts | |
| - Data formats and file preparation for PRS analysis | |
| - Statistical concepts related to polygenic architecture | |
| Always provide specific, actionable advice with examples when possible. If you're unsure about something, clearly state your limitations rather than guessing.""" | |
| PARAMETER temperature 0.7 | |
| PARAMETER top_p 0.8 | |
| PARAMETER top_k 40 | |
| PARAMETER repeat_penalty 1.05 | |
| PARAMETER stop "<|im_start|>" | |
| PARAMETER stop "<|im_end|>" | |