NEWS · MODELS · #779
Transformers adds GGUF (llama.cpp quant) support on main
Hugging Face's transformers (main branch) can now load and run GGUF quantized checkpoints using llama.cpp/ggml kernels, aiming for efficient local inference (initially optimized for Apple Silicon and Qwen3.5 models). The integration also enables serving GGUF checkpoints via transformers-serve and falls back to dequantization if compatible kernels are unavailable.
KEY POINTS
- Hugging Face's transformers (main branch) can now load and run GGUF quantized checkpoints using llama.cpp/ggml kernels, aiming for efficient local inference (initially optimized for Apple Silicon and Qwen3.5 models).
- The integration also enables serving GGUF checkpoints via transformers-serve and falls back to dequantization if compatible kernels are unavailable.
- This makes it much easier to run widely available GGUF quantized models locally through standard transformers APIs with performance approaching llama.cpp, lowering barriers to on-device inference and experimentation.
WHY IT MATTERS
This makes it much easier to run widely available GGUF quantized models locally through standard transformers APIs with performance approaching llama.cpp, lowering barriers to on-device inference and experimentation.