NielsRogge
ML @HuggingFace. Interested in deep learning, NLP. Contributed 40+ models to HuggingFace Transformers
HuggingFaceBelgium
Pinned Repositories
awesome-huggingface
Repository containing awesome resources regarding Hugging Face tooling.
coco-eval
A tiny package supporting distributed computation of COCO metrics for PyTorch models.
CogVLM
a state-of-the-art-level open visual language model
Description2Process
Transforming textual descriptions into process models using deep learning
diffusion-notes
Some notes I took when learning about diffusion models.
tapas_utils
A package containing utils for the PyTorch version of the Tapas algorithm.
transformers
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
Transformers-Tutorials
This repository contains demos I made with the Transformers library by HuggingFace.
unilm
UniLM - Unified Language Model Pre-training / Pre-training for NLP and Beyond
Vision-Transformer-papers
This repository contains an overview of important follow-up works based on the original Vision Transformer (ViT) by Google.
NielsRogge's Repositories
NielsRogge/coco-eval
A tiny package supporting distributed computation of COCO metrics for PyTorch models.
NielsRogge/notebooks
Notebooks using the Hugging Face libraries 🤗
NielsRogge/MedSAM
The official repository for MedSAM: Segment Anything in Medical Images.
NielsRogge/datasets
🤗 Fast, efficient, open-access datasets and evaluation metrics in PyTorch, TensorFlow, NumPy and Pandas
NielsRogge/DETA
Detection Transformers with Assignment
NielsRogge/diffusers
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch
NielsRogge/evaluate
A library for easily evaluating machine learning models and datasets.
NielsRogge/LiLT
Official PyTorch implementation of LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding (ACL 2022)
NielsRogge/Open-Assistant
OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
NielsRogge/ast
Code for the Interspeech 2021 paper "AST: Audio Spectrogram Transformer".
NielsRogge/BLIP
PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
NielsRogge/bros
NielsRogge/ByteTrack
[ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
NielsRogge/clip-retrieval
Easily compute clip embeddings and build a clip retrieval system with them
NielsRogge/clipseg
This repository contains the code of the CVPR 2022 paper "Image Segmentation Using Text and Image Prompts".
NielsRogge/Cream
This is a collection of our NAS and Vision Transformer work.
NielsRogge/detectron2
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
NielsRogge/FocalNet
[NeurIPS 2022] Official code for "Focal Modulation Networks"
NielsRogge/GenerativeImage2Text
GIT: A Generative Image-to-text Transformer for Vision and Language
NielsRogge/H3
Language Modeling with the H3 State Space Model
NielsRogge/MaskFormer
Per-Pixel Classification is Not All You Need for Semantic Segmentation (NeurIPS 2021, spotlight)
NielsRogge/mmcv
OpenMMLab Computer Vision Foundation
NielsRogge/mmdeploy
OpenMMLab Model Deployment Framework
NielsRogge/mmsegmentation
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
NielsRogge/Personalize-SAM
Personalize Segment Anything Model (SAM) with 1 shot in 10 seconds
NielsRogge/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.
NielsRogge/swin2sr
Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration at the Advances in Image Manipulation (AIM) workshop ECCV 2022, Tel Aviv
NielsRogge/unleashing-transformers
Code for the ECCV 2022 paper "Unleashing Transformers"
NielsRogge/VideoX
VideoX: a collection of video cross-modal models
NielsRogge/ViTMatte
Boosting Image Matting with Pretrained Plain Vision Transformers