Stars
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
A community-maintained Python framework for creating mathematical animations.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
Replace 'hub' with 'ingest' in any GitHub URL to get a prompt-friendly extract of a codebase
Statsmodels: statistical modeling and econometrics in Python
A Python implementation of global optimization with gaussian processes.
Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
Distributed Asynchronous Hyperparameter Optimization in Python
Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristi…
A data augmentations library for audio, image, text, and video.
TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...
TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/
The official Python SDK for the ElevenLabs API.
Data augmentation for NLP, presented at EMNLP 2019
Official Implementation of 'Fast AutoAugment' in PyTorch.
Contextual augmentation, a text data augmentation using a bidirectional language model.
[EMNLP 2021] Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification
Time series foreasting using Facebook's Prophet and Apache Spark