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yueyue's Projects

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Open Standard for Metadata. A Single place to Discover, Collaborate and Get your data right.

autogpt icon autogpt

An experimental open-source attempt to make GPT-4 fully autonomous.

clip icon clip

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

competition-baseline icon competition-baseline

数据挖掘、计算机视觉、自然语言处理、推荐系统竞赛知识、代码、思路

crosskd icon crosskd

CrossKD: Cross-Head Knowledge Distillation for Dense Object Detection

langchain-chatchat icon langchain-chatchat

Langchain-Chatchat(原Langchain-ChatGLM)基于 Langchain 与 ChatGLM 等语言模型的本地知识库问答 | Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge based LLM (like ChatGLM) QA app with langchain

ltsf-linear icon ltsf-linear

This is the official implementation for AAAI-23 Oral paper "Are Transformers Effective for Time Series Forecasting?"

megabyte-pytorch icon megabyte-pytorch

Implementation of MEGABYTE, Predicting Million-byte Sequences with Multiscale Transformers, in Pytorch

orbit icon orbit

A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.

pyqt icon pyqt

PyQt Examples(PyQt各种测试和例子) PyQt4 PyQt5

pytorch-gan icon pytorch-gan

PyTorch implementations of Generative Adversarial Networks.

pytorch-image-models icon pytorch-image-models

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

repvit icon repvit

RepViT: Revisiting Mobile CNN From ViT Perspective

scikit-llm icon scikit-llm

Seamlessly integrate powerful language models like ChatGPT into scikit-learn for enhanced text analysis tasks.

segment-anything icon segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

vqgan-clip icon vqgan-clip

Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.

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