5 tools
ggml-org (Georgi Gerganov and contributors) · Local LLM inference & serving
C/C++ inference engine for LLMs and vision-language models with GGUF quantized weights, Metal, CUDA, Vulkan and other backends, a CLI and an OpenAI-compatible server
Ray project (Anyscale and contributors) · Distributed & parallel computing
Open-source Python framework for distributing tasks, actors and ML workloads across a cluster, with libraries for data processing, training, tuning, serving and reinforcement learning
Hugging Face · Training & fine-tuning
Hugging Face's model-definition library for text, vision, audio, video and multimodal models, with Pipeline, Trainer and generate APIs used as the reference by training and inference engines
Unsloth AI · Training & fine-tuning
Open-source framework for fine-tuning and running LLMs with reduced memory, covering LoRA, QLoRA, full fine-tuning and RL, GGUF export, Dynamic quantizations and a local Studio/Desktop UI
vLLM project (originated at UC Berkeley Sky Computing Lab) · Local LLM inference & serving
High-throughput LLM inference and serving engine with PagedAttention, continuous batching, quantization and an OpenAI-compatible server for GPU and accelerator clusters
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