🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
- nlp
- natural-language-processing
- pytorch
- pytorch-transformers
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SGLang is a high-performance serving framework for large language models and multimodal models.
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
- semantic-search
- information-retrieval
- ai
- python
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
- nlp
- pre-trained-model
- unilm
- minilm
☁️ Build multimodal AI applications with cloud-native stack
- neural-search
- cloud-native
- deep-learning
- machine-learning
A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
- machine-translation
- speaker-recognition
- asr
- tts
Open Source framework for voice agents, multimodal apps, and realtime AI. Maintained by Daily and the community.
- ai
- real-time
- voice
- voice-assistant
NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.
PyTorch implementation of the MIDAS algorithm for single-cell multimodal data integration (Nature Biotechnology 2024).
- deep-generative-model
- deep-learning
- single-cell-data-integration
- single-cell-multiomics