Instructions to use QuantFactory/Mistral-Nemo-Base-2407-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/Mistral-Nemo-Base-2407-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/Mistral-Nemo-Base-2407-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf QuantFactory/Mistral-Nemo-Base-2407-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/Mistral-Nemo-Base-2407-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf QuantFactory/Mistral-Nemo-Base-2407-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/Mistral-Nemo-Base-2407-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf QuantFactory/Mistral-Nemo-Base-2407-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/Mistral-Nemo-Base-2407-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf QuantFactory/Mistral-Nemo-Base-2407-GGUF:Q4_K_M
Use Docker
docker model run hf.co/QuantFactory/Mistral-Nemo-Base-2407-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use QuantFactory/Mistral-Nemo-Base-2407-GGUF with Ollama:
ollama run hf.co/QuantFactory/Mistral-Nemo-Base-2407-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use QuantFactory/Mistral-Nemo-Base-2407-GGUF with Docker Model Runner:
docker model run hf.co/QuantFactory/Mistral-Nemo-Base-2407-GGUF:Q4_K_M
- Lemonade
How to use QuantFactory/Mistral-Nemo-Base-2407-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull QuantFactory/Mistral-Nemo-Base-2407-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Mistral-Nemo-Base-2407-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
- Xet hash:
- f68abf7817b2ecb1ee4b77cec434c7bc8c214535f6af1f9b7ed20e1cf08ce52e
- Size of remote file:
- 6.08 GB
- SHA256:
- d838c2f4f57588fe326b8daafe58f8b0bb50769db1f576017c41a74570cffda6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.