lightning-transformers
solo-learn
| lightning-transformers | solo-learn | |
|---|---|---|
| 1 | 3 | |
| 574 | 1,355 | |
| - | - | |
| 8.2 | 5.9 | |
| over 1 year ago | 17 days ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
lightning-transformers
-
Lightning Transformers - Train HuggingFace Transformers with PyTorch
Lightning Transformers is for users who want to train, evaluate and predict using HuggingFace models and datasets with PyTorch Lightning. Full customizability of the code using the LightningModule and Trainer, with Hydra config composition for quick and easy experimentation. No boilerplate code is required; easily swap out models, optimizers, schedulers, and more without touching the code. Check out the blog post: Training Transformers at Scale with PyTorch Lightning for more information or the documentation.
solo-learn
- [D]Use SimCLR as pretraining for image segmentation
-
[D] State-of-the-Art for Self-Supervised (Pre-)Training of CNN architectures (e.g. ResNet)?
Hello, I lost a bit of touch to the current SOTA of self-supervised pretraining of CNNs, in particular ResNet. I found this repository https://github.com/vturrisi/solo-learn that has many methods implemented but I'm not really sure where to start. My goal is to pretrain a ResNet backbone on a decently large amount of image data that comes from a certain domain and after that fine-tune it for different downstream tasks (classification, segmentation, object detection) on a subset of the data I have labels for.
-
[P] Solo-learn 1.0.3: new methods, support for transformer architectures, better evaluation, improved docs, and additional results.
Hi Reddit, the solo-learn team is back again with interesting news about its SSL library.
What are some alternatives?
lightning-hydra-template - PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡
dino - PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO
pytorch-forecasting - Time series forecasting with PyTorch
contrastive-reconstruction - Tensorflow-keras implementation for Contrastive Reconstruction (ConRec) : a self-supervised learning algorithm that obtains image representations by jointly optimizing a contrastive and a self-reconstruction loss.
lightning-hydra-template - Deep Learning project template best practices with Pytorch Lightning, Hydra, Tensorboard.
Revisiting-Contrastive-SSL - Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]
Unsupervised-Semantic-Segmentation - Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals. [ICCV 2021]
CEBRA - Learnable latent embeddings for joint behavioral and neural analysis - Official implementation of CEBRA
vectorrvnn - Data Driven method for hierarchical grouping of paths in Vector Graphics.
detrex - detrex is a research platform for DETR-based object detection, segmentation, pose estimation and other visual recognition tasks.
mmselfsup - OpenMMLab Self-Supervised Learning Toolbox and Benchmark