Instructions to use RichardErkhov/MathLLMs_-_MathCoder-L-7B-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 RichardErkhov/MathLLMs_-_MathCoder-L-7B-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 RichardErkhov/MathLLMs_-_MathCoder-L-7B-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf RichardErkhov/MathLLMs_-_MathCoder-L-7B-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 RichardErkhov/MathLLMs_-_MathCoder-L-7B-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf RichardErkhov/MathLLMs_-_MathCoder-L-7B-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 RichardErkhov/MathLLMs_-_MathCoder-L-7B-gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf RichardErkhov/MathLLMs_-_MathCoder-L-7B-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 RichardErkhov/MathLLMs_-_MathCoder-L-7B-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf RichardErkhov/MathLLMs_-_MathCoder-L-7B-gguf:Q4_K_M
Use Docker
docker model run hf.co/RichardErkhov/MathLLMs_-_MathCoder-L-7B-gguf:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use RichardErkhov/MathLLMs_-_MathCoder-L-7B-gguf with Ollama:
ollama run hf.co/RichardErkhov/MathLLMs_-_MathCoder-L-7B-gguf:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use RichardErkhov/MathLLMs_-_MathCoder-L-7B-gguf with Docker Model Runner:
docker model run hf.co/RichardErkhov/MathLLMs_-_MathCoder-L-7B-gguf:Q4_K_M
- Lemonade
How to use RichardErkhov/MathLLMs_-_MathCoder-L-7B-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull RichardErkhov/MathLLMs_-_MathCoder-L-7B-gguf:Q4_K_M
Run and chat with the model
lemonade run user.MathLLMs_-_MathCoder-L-7B-gguf-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download MathCoder-L-7B.Q2_K.gguf from RichardErkhov/MathLLMs_-_MathCoder-L-7B-gguf: direct link, hf CLI and curl.
- Browser
- Download file 2.53 GB
-
https://huggingface.co/RichardErkhov/MathLLMs_-_MathCoder-L-7B-gguf/resolve/main/MathCoder-L-7B.Q2_K.gguf
- Command line
-
hf download hf://RichardErkhov/MathLLMs_-_MathCoder-L-7B-gguf/MathCoder-L-7B.Q2_K.gguf
-
curl -L -o MathCoder-L-7B.Q2_K.gguf https://huggingface.co/RichardErkhov/MathLLMs_-_MathCoder-L-7B-gguf/resolve/main/MathCoder-L-7B.Q2_K.gguf
2.53 GB
- Xet hash:
- d243a6aa6d1bc6aa81628f24556fdf04f81a69f6e0593fbba8681d4e5ffc141f
- Size of remote file:
- 2.53 GB
- SHA256:
- 1ae55069596a4383369cc521d6d16fe70c1ebdd61a986b43b3f4c7384acf7e88
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