OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
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Updated
Jul 16, 2024 - C++
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
🔍 LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, Baichuan, Mixtral, Gemma, Phi, etc.) on Intel CPU and GPU (e.g., local PC with iGPU, discrete GPU such as Arc, Flex and Max); seamlessly integrate with llama.cpp, Ollama, HuggingFace, LangChain, LlamaIndex, DeepSpeed, vLLM, FastChat, Axolotl, etc.
👑 Easy-to-use and powerful NLP and LLM library with 🤗 Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including 🗂Text Classification, 🔍 Neural Search, ❓ Question Answering, ℹ️ Information Extraction, 📄 Document Intelligence, 💌 Sentiment Analysis etc.
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[ECCV 2024] Official implementation of the paper "Relation DETR: Exploring Explicit Position Relation Prior for Object Detection"
GPT-powered chat for documentation, chat with your documents
🚀 Accelerate training and inference of 🤗 Transformers and 🤗 Diffusers with easy to use hardware optimization tools
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
Accelerate your training with this open-source library. Optimize performance with streamlined training and serving options with JAX. 🚀
This repository contains a web application designed to execute relatively compact, locally-operated Large Language Models (LLMs).
Context aware, pluggable and customizable data protection and de-identification SDK for text and images
Neural Network Compression Framework for enhanced OpenVINO™ inference
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🔮 SuperDuper: Bring AI to your database! Build, deploy and manage any AI application directly with your existing data infrastructure, without moving your data. Including streaming inference, scalable model training and vector search.
An elegent pytorch implement of transformers
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