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* docs : center badges and links, remove Hot topics - Use <div align="center"> for GitHub-compatible centering - Add dev branches and compile times links - Remove Hot topics section Assisted-by: llama.cpp:Qwen3.6-27B * readme : remove sections * docs : center badges, remove Hot topics, extract sections, remove tools - Use <div align="center"> for GitHub-compatible centering - Add dev branches and compile times links - Add lib llama API and llama-server REST API links - Remove Hot topics section - Remove Recent API changes section - Extract XCFramework section into docs/xcframework.md - Extract Completions section into docs/completions.md - Extract Obtaining and quantizing models into docs/models.md - Remove tools usage sections (llama-cli, llama-server, etc.) - Move Contributing section to the end Assisted-by: llama.cpp:Qwen3.6-27B * cont : arrange links * cont : fix ws * cont : remove seminal papers * cont : change sample model * cont : trim-down contributing section * cont : sort backends alphabetically * cont : words * cont : add fig captions * docs : models words * readme : shorter caption * cont : fix typo * cont : add window frame to screenshot
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Obtaining and quantizing models
The Hugging Face platform hosts thousands of models compatible with llama.cpp:
You can use any llama.cpp-compatible model from Hugging Face using this CLI argument: -hf <user>/<model>[:quant]. For example:
llama cli -hf ggml-org/gemma-3-1b-it-GGUF
You can use the same CLI invocation to download from other sites, by pointing the MODEL_ENDPOINT environment variable to an endpoint compatible with the Hugging Face API.
llama.cpp can also run models you have downloaded locally to your filesystem.
After downloading a model, use the CLI tools to run it locally - see below.
llama.cpp requires the model to be stored in the GGUF file format. Models in other data formats can be converted to GGUF using the convert_*.py Python scripts in this repo.
To learn more about model quantization, read this documentation
The Hugging Face platform provides a variety of online tools for converting, quantizing and hosting models with llama.cpp:
- Use the GGUF-my-repo space to convert to GGUF format and quantize model weights to smaller sizes
- Use the GGUF-my-LoRA space to convert LoRA adapters to GGUF format (more info: https://github.com/ggml-org/llama.cpp/discussions/10123)
- Use the GGUF-editor space to edit GGUF meta data in the browser (more info: https://github.com/ggml-org/llama.cpp/discussions/9268)
- Use the Inference Endpoints to directly host
llama.cppin the cloud (more info: https://github.com/ggml-org/llama.cpp/discussions/9669)