Pytorch Libraries

156 Components & Libraries

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Pytorch Libraries

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models to perform tasks on different modalities such as text, vision, and audio. Thes…

Learn how to responsibly develop, deploy and maintain production machine learning applications.

Learn the foundations of machine learning through intuitive explanations, clean code and visualizations. Learn how to combine machine learning with software engineering to build production-grade appl…

Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

4 September 2023 - Version 1.7.1 25 May 2023 - Version 1.7.0 15 September 2022 - Version 1.6.2 1 September 2022 - Version 1.6.1 24 August 2022 - Version 1.6.0 2 June 2022 - Version 1.5.0 For the late…

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

To install the current release: Participating discussions via the following IM groups is also welcomed. Over the past few years, NNI has received thousands of feedbacks on GitHub issues, and pull req…

深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.

基于TensorFlow 2正式版！！！理论与实战结合，非常适合入门学习！！！联系邮箱(一般问题建议Github issues交流)：liangqu.long AT gmail.com 以下高校已采用本书作为专业教材或参考资料(排名不分先后)，欢迎更多高校加入！发送邮件即可索取PPT原始教案。适合零基础、希望快速入门AI的朋友，提供答疑、指导等全方位服务。

An open-source NLP research library, built on PyTorch.

An Apache 2.0 NLP research library, built on PyTorch, for developing state-of-the-art deep learning models on a wide variety of linguistic tasks. When you're ready to start your project, we…

The Unified Machine Learning Framework

Ivy is both an ML transpiler and a framework, currently supporting JAX, TensorFlow, PyTorch and Numpy. Ivy's transpiler allows you to use code from any other framework (or from any other version of t…

Low-code framework for building custom LLMs, neural networks, and other AI models

Key features: Install from PyPi. Be aware that Ludwig requires Python 3.8+. Or install with all optional dependencies: Let's fine-tune a pretrained LLaMA-2-7b large language model to follow instructi…

:mag: Haystack is an open source NLP framework to interact with your data using Transformer models and LLMs (GPT-4, ChatGPT and alike). Haystack offers production-ready tools to quickly build complex question answering, semantic search, text generation applications, and more.

This command installs everything needed for basic Pipelines that use an in-memory DocumentStore. If you want to install only the dependencies needed for model inference on your local hardware (not re…

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

Get started with W&B in four steps: That's it! Navigate to the W&B App to view a dashboard of your first W&B Experiment. Use the W&B App to compare multiple experiments in a unified…

pix2tex: Using a ViT to convert images of equations into LaTeX code.

The goal of this project is to create a learning based system that takes an image of a math formula and returns corresponding LaTeX code. To run the model you need Python 3.7+ Model checkpoints will …

Background Remover lets you Remove Background from images and video using AI with a simple command line interface that is free and open source.

python >= 3.6 python3.6-dev #or what ever version of python you use ffmpeg 4.4+ To clarify, you must install both python and whatever dev version of python you installed. IE; python3.10-dev with p…

Python code for "Probabilistic Machine learning" book by Kevin Murphy

The notebooks needed to make all the figures are available at the following locations. You can use any of the following options to install the other requirements. Run Then install manually.

Deep learning with satellite & aerial imagery

Extracting roads is challenging due to the occlusions caused by other objects and the complex traffic environment In instance segmentation, each individual 'instance' of a segmented area is given a u…

😎 Finding duplicate images made easy!

This package provides functionality to make use of hashing algorithms that are particularly good at finding exact duplicates as well as convolutional neural networks which are also adept at finding n…

Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.

Aim is an open-source, self-hosted ML experiment tracking tool designed to handle 10,000s of training runs. Aim provides a performant and beautiful UI for exploring and comparing training runs. Addit…

In this repository, I will share some useful notes and references about deploying deep learning-based models in production.

Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

State-of-the-art Deep Learning library for Time Series and Sequences. If you plan to develop tsai yourself, or want to be on the cutting edge, you can use an editable install. First install PyTorch, …

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to production models. Flexible integration for any Python script: Build …

Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.

IPython Notebook(s) and other programming tools such as Torch/Lua/D lang in demonstrating deep learning functionality. Additional PyRo tutorials: IPython Notebook(s) demonstrating scikit-learn functi…

🛠 All-in-one web-based IDE specialized for machine learning and data science.

The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on you…

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling you to thoroughly test your data and models from research to production. Deepchecks includes: For …

Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science

There are eight subjects in the curriculum, organized into four subject areas. See the "Machine Learning House" section below for detail on why these are the essential foundational subject areas: Lat…

Machine Learning Engineering Online Book

An open collection of methodologies to help with successful training of large language models and multi-modal models. This is a technical material suitable for LLM/VLM training engineers and operator…

A python library for self-supervised learning on images.

Lightly SSL is a computer vision framework for self-supervised learning. This self-supervised learning framework offers the following features: Want to jump to the tutorials and see Lightly in action…

Represent, send, store and search multimodal data

To install DocArray from the CLI, run the following command: New to DocArray? Depending on your use case and background, there are multiple ways to learn about DocArray: This is particularly benefici…