Instructions to use bartowski/xLAM-7b-r-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 bartowski/xLAM-7b-r-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 bartowski/xLAM-7b-r-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf bartowski/xLAM-7b-r-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 bartowski/xLAM-7b-r-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf bartowski/xLAM-7b-r-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 bartowski/xLAM-7b-r-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf bartowski/xLAM-7b-r-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 bartowski/xLAM-7b-r-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf bartowski/xLAM-7b-r-GGUF:Q4_K_M
Use Docker
docker model run hf.co/bartowski/xLAM-7b-r-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use bartowski/xLAM-7b-r-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bartowski/xLAM-7b-r-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": "bartowski/xLAM-7b-r-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/bartowski/xLAM-7b-r-GGUF:Q4_K_M
- Ollama
How to use bartowski/xLAM-7b-r-GGUF with Ollama:
ollama run hf.co/bartowski/xLAM-7b-r-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use bartowski/xLAM-7b-r-GGUF with Docker Model Runner:
docker model run hf.co/bartowski/xLAM-7b-r-GGUF:Q4_K_M
- Lemonade
How to use bartowski/xLAM-7b-r-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull bartowski/xLAM-7b-r-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.xLAM-7b-r-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download xLAM-7b-r-IQ3_XS.gguf from bartowski/xLAM-7b-r-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 3.02 GB
-
https://huggingface.co/bartowski/xLAM-7b-r-GGUF/resolve/main/xLAM-7b-r-IQ3_XS.gguf
- Command line
-
hf download hf://bartowski/xLAM-7b-r-GGUF/xLAM-7b-r-IQ3_XS.gguf
-
curl -L -o xLAM-7b-r-IQ3_XS.gguf https://huggingface.co/bartowski/xLAM-7b-r-GGUF/resolve/main/xLAM-7b-r-IQ3_XS.gguf
3.02 GB
- Xet hash:
- ebeeed2ec732e753f69126e00d8d8511279201db4494c54b17707530b6d064ec
- Size of remote file:
- 3.02 GB
- SHA256:
- 614da56e9b6a0daf2dd36bc53ae041688a5d14390fc775b2373b50b0a46bc5c7
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