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🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Models and examples built with TensorFlow
中英文敏感词、语言检测、中外手机/电话归属地/运营商查询、名字推断性别、手机号抽取、身份证抽取、邮箱抽取、中日文人名库、中文缩写库、拆字词典、词汇情感值、停用词、反动词表、暴恐词表、繁简体转换、英文模拟中文发音、汪峰歌词生成器、职业名称词库、同义词库、反义词库、否定词库、汽车品牌词库、汽车零件词库、连续英文切割、各种中文词向量、公司名字大全、古诗词库、IT词库、财经词库、成语词库、地名词库、…
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
PyTorch Tutorial for Deep Learning Researchers
⚡ A Fast, Extensible Progress Bar for Python and CLI
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Graph Neural Network Library for PyTorch
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Open source platform for the machine learning lifecycle
Fast and memory-efficient exact attention
Jupyter metapackage for installation, docs and chat
Python Implementation of Reinforcement Learning: An Introduction
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
A MNIST-like fashion product database. Benchmark 👇
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
A paper list of object detection using deep learning.
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.