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
File size: 1,231 Bytes
1d438c7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | 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|>"
|