Transformer Libraries

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Transformer 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…

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

: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…

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 …

💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows

txtai is an all-in-one embeddings database for semantic search, LLM orchestration and language model workflows. Embeddings databases are a union of vector indexes (sparse and dense), graph networks a…

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, …

Open-source offline translation library written in Python

Argos Translate also manages automatically pivoting through intermediate languages to translate between languages that don't have a direct translation between them installed. For example, if you have…

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…

Context aware, pluggable and customizable data protection and de-identification SDK for text and images

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provi…

Generate images from texts. In Russian

The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.

Does one of these scenarios sounds familiar to you? If so, you are one of the people we've built refinery for. refinery helps you to build better NLP models in a data-centric approach. Semi-automate …

A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch

A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch The content of this document is organized as follows: Two simpler at…

Transformer models from BERT to GPT-4, environments from Hugging Face to OpenAI. Fine-tuning, training, and prompt engineering examples. A bonus section with ChatGPT, GPT-3.5-turbo, GPT-4, and DALL-E including jump starting GPT-4, speech-to-text, text-to-speech, text to image generation with DALL-E, Google Cloud AI,HuggingGPT, and more

Last updated: November 19,2023 Just look for the Dolphin 🐬 and enjoy your ride into the future of AI! To run these notebooks on a cloud platform, just click on one of the badges in the table below or…

Learn Cloud Applied Generative AI Engineering (GenEng) using OpenAI, Gemini, Streamlit, Containers, Serverless, Postgres, LangChain, Pinecone, and Next.js

Note: If possible register your account with a company email address. Once you have a subscription id apply for Azure Open AI Service here: GenEng revolution being led by developers who build deep pr…

🏬 modelstore is a Python library that allows you to version, export, and save a machine learning model to your filesystem or a cloud storage provider.

✅ No tracking server required ✅ Upload and version all your models ✅ Manage models by domains and states ✅ Download or load straight into memory ✅ Use as a command line tool Is there a machine learni…

Repository for Project Insight: NLP as a Service

The downstream NLP tasks covered: News Classification Entity Recognition Sentiment Analysis Summarization The user can select different models from the drop down to run the inference. The users can a…

The official code repo of "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection"

Install the 'SOX' and the 'ffmpeg', we recommend that you run this code in Linux inside the Conda environment. In that, you can install them by: For the most important part: If you want to train/test…

This is where I put things I find useful that speed up my work with Machine Learning. Ever looked in your old projects to reuse those cool functions you created before? Well, this repo is designed to be a Python Library of functions I created in my previous project that can be reused. I also share some Notebooks Tutorials and Python Code Snippets.

I created this repo because I was tired of always looking up same code from older projects and I wanted to gain some experience in building a Python library. By making this available to everyone it g…

Amazon SageMaker Local Mode Examples

This repository contains examples and related resources showing you how to preprocess, train, debug your training script with breakpoints, and serve on your local machine using Amazon SageMaker Local…

Deploy-BERT-for-Sentiment-Analysis-with-FastAPI

Deploy BERT for Sentiment Analysis as REST API using FastAPI, Transformers by Hugging Face and PyTorch

Deploy a pre-trained BERT model for Sentiment Analysis as a REST API using FastAPI The model is trained to classify sentiment (negative, neutral, and positive) on a custom dataset from app reviews on…

Using data analytics of popular trading strategies and indicators, to identify best trading actions based solely on the price action.

Profitable stocks and crypto trading involves a lot of know how and experience in Technical Analysis. However, the fundamentals behind technical analysis techniques, tools, resources and effective st…

QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

Announcement video When I started to get into more advanced Machine Learning, I started to see how these famous neural network architectures(such as EfficientNet), were doing amazing things. However,…

Pytorch implementation of the paper "The Devil Is in the Details: Window-based Attention for Image Compression".

This repo defines the CNN-based models and Transformer-based models for learned image compression in "The Devil Is in the Details: Window-based Attention for Image Compression". The architecture of C…

DECIMER: Deep Learning for Chemical Image Recognition using Efficient-Net V2 + Transformer

The DECIMER 2.2 [5] (Deep lEarning for Chemical ImagE Recognition) project [1] was launched to address the OCSR problem with the latest computational intelligence methods to provide an automated open…

Extensive tutorials for the Advanced NLP Workshop in Open Data Science Conference Europe 2020. We will leverage machine learning, deep learning and deep transfer learning to learn and solve popular tasks using NLP including NER, Classification, Recommendation \ Information Retrieval, Summarization, Classification, Language Translation, Q&A and Topic Models.

Being specialized in domains like computer vision and natural language processing is no longer a luxury but a necessity which is expected of any data scientist in today’s fast-paced world! With a han…

Tutorials on machine learning, artificial intelligence, data science with math explanation and reusable code (in python and R)

Moreover, you may find here some Colab notebooks without a theoretical tutorial (yet). I decided to upload the code before I finished writing the theoretical part (this would be indicated). I am co…

Easiest way of fine-tuning HuggingFace video classification models

and supports: Tensorboard tracker is enabled by default. To add Neptune/Layer ... tracking: Before opening a PR:

🧐SwanLab: a tool for your machine learning log tracking and experiment management. Join our WeChat ⬇️

[24/01/25] 😄 We supported a new Config/Summary table component that supports parameter search. Additionally, we've used new fonts and color schemes.（v0.1.6） Requirement：Python 3.8+. For example, We w…

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