Beast code in Giters

kxqt's starred repositories

Attention-Mediators

[ECCV 2024] Efficient Diffusion Transformer with Step-wise Dynamic Attention Mediators

Language:Python2700

[ECCV2024] This is an official inference code of the paper "Glyph-ByT5: A Customized Text Encoder for Accurate Visual Text Rendering" and "Glyph-ByT5-v2: A Strong Aesthetic Baseline for Accurate Multilingual Visual Text Rendering""

Language:Jupyter NotebookApache-2.048900

awesome-free-chatgpt

🆓免费的 ChatGPT 镜像网站列表，持续更新。List of free ChatGPT mirror sites, continuously updated.

Language:PythonMIT1792600

vpncn.github.io

2024**翻墙软件VPN推荐以及科学上网避坑，稳定好用。对比SSR机场、蓝灯、V2ray、老王VPN、VPS搭建梯子等科学上网与翻墙软件，**最新科学上网翻墙梯子VPN下载推荐，访问Chatgpt。

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VAR

[GPT beats diffusion🔥] [scaling laws in visual generation📈] Official impl. of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction". An *ultra-simple, user-friendly yet state-of-the-art* codebase for autoregressive image generation!

Language:PythonMIT403100

DesignEdit

Code for DesignEdit

Language:PythonMIT30200

Rethinking-Text-Segmentation

[CVPR 2021] Rethinking Text Segmentation: A Novel Dataset and A Text-Specific Refinement Approach

Language:Python24500

Rank-DETR

[NeurIPS 2023] Rank-DETR for High Quality Object Detection

Language:PythonApache-2.08600

Expedit-Mask2Former

[NeurIPS2022] This is the official implementation of the paper "Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning" on Mask2Former.

Language:PythonNOASSERTION500

Expedit-Video-Swin-Transformer

[NeurIPS2022] This is the official implementation of the paper "Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning" on Video Swin Transformer.

Language:PythonApache-2.0200

Expedit-OneFormer

[NeurIPS2022] This is the official implementation of the paper "Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning" on OneFormer.

Language:Jupyter NotebookMIT100

Mask2Former

Code release for "Masked-attention Mask Transformer for Universal Image Segmentation"

Language:PythonMIT247700

pyllama

LLaMA: Open and Efficient Foundation Language Models

Language:PythonGPL-3.0280400

Awesome-Anything

General AI methods for Anything: AnyObject, AnyGeneration, AnyModel, AnyTask, AnyX

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Expedit-SAM

[NeurIPS2022] This is the official implementation of the paper "Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning" for SAM.

Language:Jupyter NotebookApache-2.08100

Prompt-Segment-Anything

This is an implementation of zero-shot instance segmentation using Segment Anything.

Language:PythonApache-2.029800

JARVIS

JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf

Language:PythonMIT2357400

Prompt-Engineering-Guide

🐙 Guides, papers, lecture, notebooks and resources for prompt engineering

Language:MDXMIT4803900

openai-cookbook

Examples and guides for using the OpenAI API

Language:MDXMIT5877800

Make-It-3D

[ICCV 2023] Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior

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crawlingathome-gpu-hcloud

GPU controlled Hetzner Cloud workers swarm for Crawling@Home project

Language:Jupyter NotebookMIT4900

Expedit-DINO

[NeurIPS2022] This is the official implementation of the paper "Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning" on DINO and MaskDINO.

Language:PythonApache-2.0800

ReAct

[ICLR 2023] ReAct: Synergizing Reasoning and Acting in Language Models

Language:Jupyter NotebookMIT188700

Expedit-Segmenter

[NeurIPS2022] This is the official implementation of the paper "Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning" on Segmenter.

Language:Jupyter NotebookApache-2.0500

Expedit-DPT

[NeurIPS2022] This is the official implementation of the paper "Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning" on DPT.

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Expedit-SWAG

[NeurIPS2022] This is the official implementation of the paper "Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning" on SWAG.

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SparK

[ICLR'23 Spotlight🔥] The first successful BERT/MAE-style pretraining on any convolutional network; Pytorch impl. of "Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling"

Language:PythonMIT142400

scenic

Scenic: A Jax Library for Computer Vision Research and Beyond

Language:PythonApache-2.0326400

H-Deformable-DETR

[CVPR2023] This is the official implementation of H-Deformable-DETR w/ ViT-L (MAE).

Language:PythonMIT600

H-Deformable-DETR

[CVPR2023] This is an official implementation of paper "DETRs with Hybrid Matching".

Language:PythonMIT25700