| Name | Version | Summary | date |
| pysmatch |
0.9 |
Propensity Score Matching(PSM) on python |
2024-12-18 03:39:42 |
| dynesty |
2.1.5 |
A dynamic nested sampling package for computing Bayesian posteriors and evidences. |
2024-12-17 20:07:48 |
| anemoi-inference |
0.4.3 |
A package to hold various functions to support training of ML models. |
2024-12-14 14:57:36 |
| geo-espresso |
0.3.19 |
Earth Science PRoblems for the Evaluation of Strategies, Solvers and Optimizers |
2024-12-12 05:16:16 |
| triton-model-navigator |
0.13.0 |
Triton Model Navigator: An inference toolkit for optimizing and deploying machine learning models and pipelines on the Triton Inference Server and PyTriton. |
2024-12-06 14:40:12 |
| figaro |
1.7.2 |
FIGARO: Fast Inference for GW Astronomy, Research & Observations |
2024-12-04 11:39:06 |
| tritony |
0.0.19 |
Tiny configuration for Triton Inference Server |
2024-12-04 06:52:20 |
| inference-server |
1.3.2 |
Deploy your AI/ML model to Amazon SageMaker for Real-Time Inference and Batch Transform using your own Docker container image. |
2024-11-28 16:30:44 |
| tritonclient |
2.52.0 |
Python client library and utilities for communicating with Triton Inference Server |
2024-11-26 04:27:23 |
| triton-model-analyzer |
1.46.0 |
Triton Model Analyzer is a tool to profile and analyze the runtime performance of one or more models on the Triton Inference Server |
2024-11-26 04:23:27 |
| hot-fair-utilities |
2.0.6 |
Utilities for AI - Assisted Mapping fAIr |
2024-11-25 21:09:42 |
| azcausal |
0.2.4.2 |
Casual Inference |
2024-11-22 00:01:34 |
| raynest |
1.0.6 |
raynest: Parallel nested sampling based on ray |
2024-11-21 15:22:06 |
| optimum-tpu |
0.2.0 |
Optimum TPU is the interface between the Hugging Face Transformers library and Google Cloud TPU devices. |
2024-11-20 13:07:21 |
| aquila-borg |
2.1.2 |
ARES/BORG engine packaged in a Python module |
2024-11-18 07:40:35 |
| optimum-neuron |
0.0.26 |
Optimum Neuron is the interface between the Hugging Face Transformers and Diffusers libraries and AWS Trainium and Inferentia accelerators. It provides a set of tools enabling easy model loading, training and inference on single and multiple neuron core settings for different downstream tasks. |
2024-11-15 15:54:07 |
| estimagic |
0.5.1 |
Tools to solve difficult numerical optimization problems. |
2024-11-13 17:11:56 |
| optimagic |
0.5.1 |
Tools to solve difficult numerical optimization problems. |
2024-11-13 17:03:15 |
| gemlib |
0.12.1 |
GEMlib scientific compute library for epidemic modelling |
2024-11-12 05:27:28 |
| pyabc |
0.12.15 |
Distributed, likelihood-free ABC-SMC inference |
2024-11-11 09:22:18 |