| Name | Version | Summary | date |
| nitec |
0.0.2 |
The official PyTorch implementation of NITEC for eye contact detection. |
2023-11-20 10:00:48 |
| neurocode |
1.0.0 |
🧠EEG/MEG self-supervised learning toolbox. |
2023-11-19 15:49:06 |
| proteinshake |
0.3.14 |
Protein structure datasets for machine learning. |
2023-11-18 19:07:54 |
| braindecode |
0.8.1 |
Deep learning software to decode EEG, ECG or MEG signals |
2023-11-14 13:45:31 |
| diffusers-api |
0.0.1 |
diffusers-api: A Python API for Diffusion Models |
2023-11-10 23:00:54 |
| run-stardist |
0.0.2 |
Train and use StarDist models |
2023-11-06 16:26:48 |
| colab2pdf |
1.0.0a14 |
Convert Your Colab Notebook to a PDF. One-Minute Install. Zero Configuration. |
2023-11-05 15:12:32 |
| plato-learn |
1.0 |
Packaged version of the Plato framework for federated learning research |
2023-11-04 02:00:56 |
| hypertune |
1.1.0 |
A library for performing hyperparameter optimization with Polyaxon. |
2023-11-02 08:58:15 |
| autocare-dlt |
0.2.6 |
Autocare Tx Model |
2023-10-25 07:36:13 |
| fluidml |
0.3.4 |
FluidML is a lightweight framework for developing machine learning pipelines. Focus only on your tasks and not the boilerplate! |
2023-10-20 19:26:39 |
| wow-ai-vision |
0.0.4 |
A set of easy-to-use utils that will come in handy in any Computer Vision project |
2023-10-19 09:44:57 |
| adam-lr-decay |
0.0.8 |
Adam Layer-wise LR Decay |
2023-10-18 16:56:44 |
| rwkv2onnx |
0.0.13 |
RWKV to ONNX (powered by Faster RWKV) |
2023-10-18 12:41:52 |
| kerastorch |
1.0.3 |
llm model process for pytorch |
2023-10-15 01:38:36 |
| llmtorch |
1.0.22 |
llm model process for pytorch |
2023-10-09 01:59:24 |
| xn-ultralytics |
1.0.3 |
This is a public fork of Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification. Free for anyone to use, for non-commercial purposes. |
2023-10-03 21:47:24 |
| vqa-package |
0.1.0 |
Visual Question Answering (VQA) package |
2023-09-28 09:05:16 |
| supertriplets |
1.0.6 |
Torch Multimodal Supervised Triplet Learning Toolbox |
2023-09-25 21:12:47 |
| ccsd |
0.3.3 |
CCSD (Combinatorial Complex Score-based Diffusion) is a sophisticated score-based diffusion model designed to generate Combinatorial Complexes using Stochastic Differential Equations. This cutting-edge approach enables the generation of complex objects with higher-order structures and relations, thereby enhancing our ability to learn underlying distributions and produce more realistic objects. |
2023-09-18 09:25:22 |