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

Libraries

How to use muhammadmuneeb007/PolygenicRiskScoresGPT with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="muhammadmuneeb007/PolygenicRiskScoresGPT",
	filename="model-q4_k_m.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use muhammadmuneeb007/PolygenicRiskScoresGPT with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf muhammadmuneeb007/PolygenicRiskScoresGPT:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf muhammadmuneeb007/PolygenicRiskScoresGPT:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf muhammadmuneeb007/PolygenicRiskScoresGPT:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf muhammadmuneeb007/PolygenicRiskScoresGPT:Q4_K_M

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/PolygenicRiskScoresGPT:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf muhammadmuneeb007/PolygenicRiskScoresGPT:Q4_K_M

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/PolygenicRiskScoresGPT:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf muhammadmuneeb007/PolygenicRiskScoresGPT:Q4_K_M

Use Docker

docker model run hf.co/muhammadmuneeb007/PolygenicRiskScoresGPT:Q4_K_M

LM Studio
Jan
Ollama
How to use muhammadmuneeb007/PolygenicRiskScoresGPT with Ollama:
```
ollama run hf.co/muhammadmuneeb007/PolygenicRiskScoresGPT:Q4_K_M
```

Unsloth Studio

How to use muhammadmuneeb007/PolygenicRiskScoresGPT 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/PolygenicRiskScoresGPT 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/PolygenicRiskScoresGPT to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for muhammadmuneeb007/PolygenicRiskScoresGPT to start chatting

How to use muhammadmuneeb007/PolygenicRiskScoresGPT with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf muhammadmuneeb007/PolygenicRiskScoresGPT:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "muhammadmuneeb007/PolygenicRiskScoresGPT:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use muhammadmuneeb007/PolygenicRiskScoresGPT with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf muhammadmuneeb007/PolygenicRiskScoresGPT:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default muhammadmuneeb007/PolygenicRiskScoresGPT:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use muhammadmuneeb007/PolygenicRiskScoresGPT with Docker Model Runner:
```
docker model run hf.co/muhammadmuneeb007/PolygenicRiskScoresGPT:Q4_K_M
```

Lemonade

How to use muhammadmuneeb007/PolygenicRiskScoresGPT with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull muhammadmuneeb007/PolygenicRiskScoresGPT:Q4_K_M

Run and chat with the model

lemonade run user.PolygenicRiskScoresGPT-Q4_K_M

List all available models

lemonade list

muhammadmuneeb007 commited on Jul 3, 2025

Commit

da3bd6a

verified ·

1 Parent(s): 197a311

Upload 3 files

Browse files

Files changed (4) hide show

.gitattributes +2 -0
Modelfile +32 -0
model-q4_k_m.gguf +3 -0
model.gguf +3 -0

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@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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 *.zip filter=lfs diff=lfs merge=lfs -text
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+FROM ./model-q4_k_m.gguf
+TEMPLATE """<|system|>
+{{ .System }}<|end|>
+<|user|>
+{{ .Prompt }}<|end|>
+<|assistant|>
+"""
+SYSTEM """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 0.9
+PARAMETER top_k 40
+PARAMETER repeat_penalty 1.1
+PARAMETER stop "<|end|>"
+PARAMETER stop "<|system|>"
+PARAMETER stop "<|user|>"
+PARAMETER stop "<|assistant|>"

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