EATN

? Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

AI 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.

[CVPR2023] Blur Interpolation Transformer for Real-World Motion from Blur

《李宏毅深度学习教程》（李宏毅老师推荐?，苹果书?），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases

Natural Language Processing Tutorial for Deep Learning Researchers

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"

? 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, ?? Information Extraction, ? Document Intelligence, ? Sentiment Analysis etc.

A curated list of Site Reliability and Production Engineering resources.

? Scalable embedding, reasoning, ranking for images and sentences with CLIP