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Model & Inference Framework大语言模型Python

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A Rust-based cross-platform CLI tool that right-sizes LLM models to your system's RAM, CPU, and GPU by detecting specs and recommending optimal models and quantization strategies. Covers 206 models from 57 providers.

Model & Inference Framework大语言模型Rust

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An open-source framework for large language model evaluations from the UK AI Safety Institute, featuring a modular Datasets/Solvers/Scorers architecture, multi-model/tool support, sandboxed execution, and 100+ pre-built benchmarks.

Model & Inference FrameworkSDKAI Agents

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On-device full-stack AI SDK for Flutter with LLM, Vision, Speech, Image Gen, and RAG; features compute budget contracts and adaptive QoS with zero cloud dependency.

大语言模型MultimodalSDK

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An open-source framework for building, evaluating, and training general multi-agent systems. Features natural language agent creation, distributed reinforcement learning training pipeline, and complex environment interactions. Ranks top on authoritative benchmarks including GAIA, OSWorld, and VisualWebArena.

OtherMultimodal大语言模型

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An open-source AI monitoring and governance engine providing LLM hallucination detection, PII identification, prompt injection defense, and traditional ML model evaluation, featuring real-time guardrails and OpenInference support.

Model & Inference FrameworkMachine Learning大语言模型

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Smart AI model cascading library using speculative execution to dynamically select optimal models, achieving 40-85% cost savings and 2-10x latency reduction.

SDK大语言模型AI Agents

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A plug-and-play multi-object tracking (MOT) Python library offering modular implementations of classic algorithms like SORT and ByteTrack. Features a detector-agnostic design compatible with any object detection model (YOLO, DETR, etc.), supporting video files, cameras, RTSP streams, and more. Provides unified CLI tools and Python API with built-in evaluation metrics (CLEAR, HOTA, Identity).

MultimodalDeep LearningSDK

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An interactive open-access textbook on Machine Learning Systems engineering from Harvard University, integrating the TinyTorch framework with hands-on edge deployment labs, covering the full spectrum from ML fundamentals to system optimization.

OtherDeep LearningMachine Learning

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Official code repository for the O'Reilly book "Hands-On Large Language Models". Features 12 core chapters and bonus content covering Tokens, Transformers, RAG, and Fine-tuning. Includes 300+ illustrations and runnable Jupyter Notebooks optimized for Colab and local environments.

Natural Language ProcessingRAG大语言模型

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