The Build Chain and Runtime Baselines These are the current minimal operating system and compiler versions to run and compile LibreOffice, also used by the TDF builds: Windows: Runtime: Windows 10 Build: Cygwin + Visual Studio 2019 version 16.10 macOS: Runtime: 10.15 (11 for aarch64) Bu...
The fine-tuned model can be evaluated on downstream natural language understanding tasks using few-shot in-context learning. Before running evaluation, make sure you have installed OpenICL: git clone https://github.com/Shark-NLP/OpenICLcdOpenICL pip install -e. Afterwards, we can run evaluation ...
https://github.com/dmlc/GNNLens2 RNAGlib: A package to facilitate construction, analysis, visualization and machine learning on RNA 2.5D Graphs. Includes a pre-built dataset: https://rnaglib.cs.mcgill.ca OpenHGNN: Model zoo and benchmarks for Heterogeneous Graph Neural Networks. https://...
pip install git+https://github.com/rlworkgroup/metaworld.git@a0009ed9a208ff9864a5c1368c04c273bb20dd06#egg=metaworld DMCR We adopt the original DMCR implementation provided byQDataand integrated it into our codebase. You need to additionally download the assets of DMCR fromhereand move them...
Public release of the Image Matching Benchmark: https://image-matching-challenge.github.io - ubc-vision/image-matching-benchmark
Acknowledgement We appreciate the following github repos for their valuable codebase: Forecasting: https://github.com/thuml/Autoformer Anomaly Detection: https://github.com/thuml/Anomaly-Transformer Classification: https://github.com/thuml/Flowformer About...
Strong baselines for bitemporal and single-temporal supervised change detection. A clean codebase for weakly-supervised change detection. Support both bitemporal and single-temporal supervised settings Getting Started InstallEVer pip install ever-beta==0.2.3 ...
This project is a fork of the GEM projecthttps://github.com/facebookresearch/GradientEpisodicMemoryin order to reproduce baselines from their paper. These baselines have been copied into the model/ directory of this repository. Our output and logging mechanisms for all models follow the same forma...
Improved baselines with momentum contrastive learning. An empirical study of training self-supervised vision transformers. In CVPR, 2021 Domain generalization by seeking flat minima. In NeurIPS, 2021. Learning graph embeddings for compositional zero-shot learning. In CVPR, 2021 ...
First, clone the repo with (if you are in China and Github is slow, you can use the mirror inGitee): git clone https://github.com/kwai/DouZero.git Make sure you have python 3.6+ installed. Install dependencies: We recommend installing the stable version of DouZero with ...