1.vllm-project / vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
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17 repositories by Attention Score · Oct 4, 2026 – Nov 2, 2026 (UTC)
A high-throughput and memory-efficient inference and serving engine for LLMs
Make videos on the computer you already own. FreeVideo runs MiniMax H3 in as little as 8 GB of VRAM and 16 GB of RAM, and adapts its acceleration path to your hardware.
SGLang is a high-performance serving framework for large language models and multimodal models.
Open decision models from 0.8B to 27B: a calibrated probability for every option in one pass, and a short thought only when unsure. Engine for vLLM, llama.cpp and MLX.
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Nano vLLM
Machine Learning Engineering Open Book
Don't memorize ML. Understand it from first principles including Inference, Cuda, Deep Learning, Data Science and Reinforcement Learning
Infrastructure for continually self‑improving agents
LMCache: Supercharge Your LLM with the Fastest KV Cache Layer
Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
The Triton Inference Server provides an optimized cloud and edge inferencing solution.
Making large AI models cheaper, faster and more accessible
PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection with training, validation, inference, and multi-format export.
Superduper: End-to-end framework for building custom AI applications and agents.
Large Language Model Text Generation Inference