| Name | Version | Summary | date |
| vishuml |
0.1.7 |
A machine learning library implementing algorithms from scratch |
2025-08-11 03:40:34 |
| zenml-nightly |
0.84.2.dev20250811 |
ZenML: Write production-ready ML code. |
2025-08-11 00:55:27 |
| img2dataset |
1.47.0 |
Easily turn a set of image urls to an image dataset |
2025-08-09 22:07:23 |
| PyTimbre |
1.0.1.3 |
Python conversion of Timbre Toolbox |
2025-08-09 00:53:50 |
| b10-xgrammar |
0.1.22 |
Efficient, Flexible and Portable Structured Generation |
2025-08-08 23:28:16 |
| spatialreasoners |
1.0.0 |
SpatialReasoners: A framework for training Spatial Reasoning Models in any domain |
2025-08-08 20:46:56 |
| gradio |
5.42.0 |
Python library for easily interacting with trained machine learning models |
2025-08-08 20:22:08 |
| ntloss |
0.0.3 |
Number Token Loss - A regression-alike loss to improve numerical reasoning in language models |
2025-08-08 17:13:28 |
| outlines |
1.2.2 |
Probabilistic Generative Model Programming |
2025-08-08 13:14:22 |
| zenml |
0.84.2 |
ZenML: Write production-ready ML code. |
2025-08-06 15:28:24 |
| nkululeko |
0.97.3 |
Machine learning audio prediction experiments based on templates |
2025-08-06 11:16:47 |
| hpsv3 |
1.0.0 |
HPSv3: Towards Wide-Spectrum Human Preference Score - A VLM-based preference model for image quality assessment |
2025-08-06 03:11:41 |
| phiml |
1.14.1 |
Unified API for machine learning |
2025-08-02 21:33:13 |
| mlrl-testbed-sklearn |
0.12.3 |
Adds support for the scikit-learn framework to the package "mlrl-testbed" |
2025-08-02 16:56:40 |
| mlrl-testbed |
0.12.3 |
Provides utilities for the training and evaluation of machine learning algorithms |
2025-08-02 16:56:38 |
| mlrl-seco |
0.12.3 |
A scikit-learn implementation of a Separate-and-Conquer (SeCo) multi-label rule learning algorithm |
2025-08-02 16:56:23 |
| mlrl-common |
0.12.3 |
Provides common modules to be used by different types of multi-label rule learning algorithms |
2025-08-02 16:56:04 |
| neurolite |
0.2.0 |
AI/ML/DL/NLP productivity library for minimal-code machine learning workflows |
2025-08-02 12:14:37 |
| aenet-gpr |
1.8.8 |
Atomistic simulation tools based on Gaussian Processes Regression |
2025-08-02 04:02:26 |
| jrjModelRegistry |
1.0.13 |
True way to save and serve python models |
2025-07-31 19:38:17 |