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 Studio
How to use pmysl/c4ai-command-r-plus-GGUF 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 pmysl/c4ai-command-r-plus-GGUF 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 pmysl/c4ai-command-r-plus-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for pmysl/c4ai-command-r-plus-GGUF to start chatting
- 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
Cannot load.
Traceback (most recent call last):
File "C:\text-generation-webui-main\text-generation-webui-main\modules\ui_model_menu.py", line 245, in load_model_wrapper
shared.model, shared.tokenizer = load_model(selected_model, loader)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\text-generation-webui-main\text-generation-webui-main\modules\models.py", line 87, in load_model
output = load_func_maploader
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\text-generation-webui-main\text-generation-webui-main\modules\models.py", line 261, in llamacpp_loader
model, tokenizer = LlamaCppModel.from_pretrained(model_file)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\text-generation-webui-main\text-generation-webui-main\modules\llamacpp_model.py", line 102, in from_pretrained
result.model = Llama(**params)
^^^^^^^^^^^^^^^
File "C:\text-generation-webui-main\text-generation-webui-main\installer_files\env\Lib\site-packages\llama_cpp_cuda\llama.py", line 311, in init
self._model = _LlamaModel(
^^^^^^^^^^^^
File "C:\text-generation-webui-main\text-generation-webui-main\installer_files\env\Lib\site-packages\llama_cpp_cuda_internals.py", line 55, in init
raise ValueError(f"Failed to load model from file: {path_model}")
ValueError: Failed to load model from file: models\command-r-plus-Q5_K_M.gguf
This is due to fact that version of llama-cpp-python used by oobabooga/text-generation-webui does not yet support this model. You can try to build it yourself or wait for an update