| Name | Version | Summary | date |
| mlkit-lyt |
0.0.3 |
Machine Learning in Python |
2023-12-28 20:26:55 |
| plotsandgraphs |
0.1.4 |
Create plots and graphs for your Machine Learning projects. |
2023-12-28 11:28:31 |
| rest-model-service |
0.6.0 |
RESTful service for hosting machine learning models. |
2023-12-28 03:53:26 |
| nendo_plugin_musicgen |
0.1.3 |
Nendo MusicGen plugin: A state-of-the-art controllable text-to-music model (by Meta Research) |
2023-12-24 07:49:40 |
| LibreAssist |
0.0.1 |
An open-source library LibreAssist is a Local Assistance here to help you with your needs on your personal computer |
2023-12-23 13:59:09 |
| ml-verbs |
0.0.4 |
Generic interfaces for machine learning |
2023-12-23 09:11:47 |
| test-sw-12241 |
0.0.1 |
Python library for streamlined tracking and management of AI training processes. |
2023-12-22 14:11:49 |
| nendo_plugin_quantize_core |
0.1.4 |
Nendo Plugin for audio quantization with grid detection and time-stretching |
2023-12-22 11:12:58 |
| nendo_plugin_loopify |
0.1.2 |
Nendo plugin for automatic audio loop extraction. |
2023-12-22 11:12:05 |
| SmartPipeline |
0.7.3 |
A framework for fast developing scalable data pipelines following a simple design pattern |
2023-12-20 23:34:13 |
| sparsify |
1.6.1 |
Easy-to-use UI for automatically sparsifying neural networks and creating sparsification recipes for better inference performance and a smaller footprint |
2023-12-20 14:28:37 |
| swanlab-action-test |
0.0.5 |
Python library for streamlined tracking and management of AI training processes. |
2023-12-20 13:53:05 |
| audonnx |
0.7.0 |
Deploy models in ONNX format |
2023-12-18 10:47:30 |
| netwk |
2.12.5 |
Create fast, optimized, and easy-to-use neural networks. |
2023-12-17 17:08:11 |
| dropgrad-dingo-actual |
0.1.0 |
A PyTorch implementation of DropGrad regularization. |
2023-12-16 10:59:56 |
| dropgrad |
0.1.0 |
A PyTorch implementation of DropGrad regularization. |
2023-12-16 10:59:55 |
| bluemoonai |
0.0.0 |
BlueMoon AI: Open-source Text to Image Generative AI. Transform text into stunning visuals effortlessly. Free to use and contribute on GitHub. |
2023-12-16 08:31:18 |
| k-inertia |
1.0.0 |
K-Inertia: A User-Friendly Machine Learning Library K-Inertia or Kavish Inertia is a Python machine learning library designed for simplicity and ease of use. With a focus on user-friendly interfaces, K-Inertia provides implementations of various machine learning algorithms, including regression, logistic regression, k-nearest neighbors, naive Bayes, support vector machines, and k-means clustering. |
2023-12-16 07:13:18 |
| knertia |
0.0.5 |
K-Inertia: A User-Friendly Machine Learning Library K-Inertia or Kavish Inertia is a Python machine learning library designed for simplicity and ease of use. With a focus on user-friendly interfaces, K-Inertia provides implementations of various machine learning algorithms, including regression, logistic regression, k-nearest neighbors, naive Bayes, support vector machines, and k-means clustering. |
2023-12-15 20:20:19 |
| moduler |
0.0.5 |
|
2023-12-14 14:22:26 |