Instructions to use muhammadmuneeb007/BioStarsGPT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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

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 new

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

BioStarsGPT / Modelfile

muhammadmuneeb007

Upload 15 files

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	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\|>"