Instructions to use QuantFactory/rho-math-7b-v0.1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use QuantFactory/rho-math-7b-v0.1-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf QuantFactory/rho-math-7b-v0.1-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf QuantFactory/rho-math-7b-v0.1-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf QuantFactory/rho-math-7b-v0.1-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf QuantFactory/rho-math-7b-v0.1-GGUF: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 QuantFactory/rho-math-7b-v0.1-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf QuantFactory/rho-math-7b-v0.1-GGUF: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 QuantFactory/rho-math-7b-v0.1-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf QuantFactory/rho-math-7b-v0.1-GGUF:Q4_K_M
Use Docker
docker model run hf.co/QuantFactory/rho-math-7b-v0.1-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use QuantFactory/rho-math-7b-v0.1-GGUF with Ollama:
ollama run hf.co/QuantFactory/rho-math-7b-v0.1-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use QuantFactory/rho-math-7b-v0.1-GGUF with Docker Model Runner:
docker model run hf.co/QuantFactory/rho-math-7b-v0.1-GGUF:Q4_K_M
- Lemonade
How to use QuantFactory/rho-math-7b-v0.1-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull QuantFactory/rho-math-7b-v0.1-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.rho-math-7b-v0.1-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download rho-math-7b-v0.1.Q3_K_L.gguf from QuantFactory/rho-math-7b-v0.1-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 3.82 GB
-
https://huggingface.co/QuantFactory/rho-math-7b-v0.1-GGUF/resolve/main/rho-math-7b-v0.1.Q3_K_L.gguf
- Command line
-
hf download hf://QuantFactory/rho-math-7b-v0.1-GGUF/rho-math-7b-v0.1.Q3_K_L.gguf
-
curl -L -o rho-math-7b-v0.1.Q3_K_L.gguf https://huggingface.co/QuantFactory/rho-math-7b-v0.1-GGUF/resolve/main/rho-math-7b-v0.1.Q3_K_L.gguf
3.82 GB
- Xet hash:
- 66607e4521d80b1815eaa17ce76909945be7dbb6fba771fb965f6cf84c912e67
- Size of remote file:
- 3.82 GB
- SHA256:
- 75fb7654fb5c581358f3aa6d6bc5ef0147f058e5f5996720fb58782830ae42b3
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