| Name | Version | Summary | date |
| swanlab |
0.6.6 |
Python library for streamlined tracking and management of AI training processes. |
2025-07-08 13:43:35 |
| gradio |
5.22.0 |
Python library for easily interacting with trained machine learning models |
2025-03-18 21:52:51 |
| flowcept |
0.7.18 |
Capture and query workflow provenance data using data observability |
2025-02-28 00:04:53 |
| zntrack |
0.8.4 |
Create, Run and Benchmark DVC Pipelines in Python |
2025-02-20 16:52:41 |
| ipsuite |
0.2.4 |
A suite of tools for machine learned interatomic potentials. |
2025-02-17 17:03:27 |
| conda-store |
2025.2.2 |
conda-store client |
2025-02-11 23:13:20 |
| ProvSense |
1.0.2 |
ProvSense is a Python library for managing knowledge graph provenance. It enables efficient comparison of files, tracking changes, and enforcing provenance rules to ensure data integrity and traceability. Ideal for researchers and developers, ProvSense promotes transparency and accountability in data-driven workflows. |
2025-02-07 21:13:22 |
| dvclive |
3.48.2 |
Experiments logger for ML projects. |
2025-02-06 04:44:17 |
| gofigr |
0.19.0 |
GoFigr client library |
2024-12-25 10:27:07 |
| staged-script |
2.0.1 |
A Python package enabling the development of robust automation scripts that are subdivided into stages. |
2024-12-17 17:42:13 |
| mlipx |
0.1.3 |
Machine-Learned Interatomic Potential eXploration |
2024-12-12 14:13:35 |
| e2clab |
3.3.1 |
Your Edge-to-Cloud laboratory |
2024-12-04 13:06:25 |
| dvc |
3.58.0 |
Git for data scientists - manage your code and data together |
2024-12-01 16:53:53 |
| swanboard |
0.1.6 |
Dashboard for SwanLab. |
2024-11-24 09:14:15 |
| snapper-ml |
0.4.1 |
A framework for reproducible machine learning |
2024-11-12 18:25:51 |
| fairscape-cli |
1.0.2 |
A utility for packaging objects and validating metadata for FAIRSCAPE |
2024-10-30 17:25:06 |
| expyrun |
0.2.0 |
Run reproducible experiments from yaml configuration file |
2024-10-24 14:25:36 |
| gradio-rich-textbox |
0.4.3 |
Gradio custom component for rich text input |
2024-10-21 16:27:26 |
| gradio-imageslider-momen |
0.0.32 |
A Gradio component for comparing two images. This component can be used in several ways: - as a **unified input / output** where users will upload a single image and an inference function will generate an image it can be compared to (see demo), - as a **manual upload input** allowing users to compare two of their own images (which can then be passed along elsewhere, e.g. to a model), - as **static output component** allowing users to compare two images generated by an inference function. |
2024-10-15 20:56:35 |
| sierra-research |
1.3.11 |
Automation framework for the scientific method in AI research |
2024-09-23 16:28:23 |