Instructions to use pmysl/c4ai-command-r-plus-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 pmysl/c4ai-command-r-plus-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 pmysl/c4ai-command-r-plus-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf pmysl/c4ai-command-r-plus-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 pmysl/c4ai-command-r-plus-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf pmysl/c4ai-command-r-plus-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 pmysl/c4ai-command-r-plus-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf pmysl/c4ai-command-r-plus-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 pmysl/c4ai-command-r-plus-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf pmysl/c4ai-command-r-plus-GGUF:Q4_K_M
Use Docker
docker model run hf.co/pmysl/c4ai-command-r-plus-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use pmysl/c4ai-command-r-plus-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "pmysl/c4ai-command-r-plus-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "pmysl/c4ai-command-r-plus-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/pmysl/c4ai-command-r-plus-GGUF:Q4_K_M
- Ollama
How to use pmysl/c4ai-command-r-plus-GGUF with Ollama:
ollama run hf.co/pmysl/c4ai-command-r-plus-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use pmysl/c4ai-command-r-plus-GGUF with Docker Model Runner:
docker model run hf.co/pmysl/c4ai-command-r-plus-GGUF:Q4_K_M
- Lemonade
How to use pmysl/c4ai-command-r-plus-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull pmysl/c4ai-command-r-plus-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.c4ai-command-r-plus-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
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Download README.md from pmysl/c4ai-command-r-plus-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 440 Bytes
-
https://huggingface.co/pmysl/c4ai-command-r-plus-GGUF/resolve/080748d9979ab2a1a689f4ad00197b75a996141b/README.md
- Command line
-
hf download hf://pmysl/c4ai-command-r-plus-GGUF@080748d9979ab2a1a689f4ad00197b75a996141b/README.md
-
curl -L -o README.md https://huggingface.co/pmysl/c4ai-command-r-plus-GGUF/resolve/080748d9979ab2a1a689f4ad00197b75a996141b/README.md
440 Bytes
metadata
license: cc-by-nc-4.0
Command R+ GGUF
Description
This repository contains GGUF weights for the llama.cpp
Concatenating Weights
For every variant (except Q2_K), you must concatenate the weights, as they exceed the 50 GB single file size limit on HuggingFace. You can accomplish this using the cat command on Linux (example for the Q3 variant):
cat command-r-plus-Q3_K_L-0000* > command-r-plus-Q3_K_L.gguf