transformers
FrameworkOpen-source projects built with transformers
There are currently 33 open-source projects built with transformers, with a combined total of 426.8k GitHub stars. The most common language among these projects is Python.
Showing 33 open-source projects
A comprehensive collection of Chinese NLP resources, datasets, tools, and pre-trained models for developers and researchers.
A latent text-to-image diffusion model that generates detailed images from text prompts, running on GPUs with at least 10GB VRAM.
An open-source AI engine that runs LLMs, vision, voice, and image/video models on any hardware with drop-in OpenAI API compatibility.
An open platform for training, serving, and evaluating large language model based chatbots.
A transformer-based text-to-audio model that generates realistic multilingual speech, music, and sound effects.
A unified Python library for explaining any machine learning model's predictions using Shapley values from game theory.
A fast, memory-efficient reimplementation of OpenAI's Whisper speech-to-text model using CTranslate2.
A Python framework for computing and training state-of-the-art text embeddings, rerankers, and sparse encoders.
A comprehensive library for post-training foundation models using reinforcement learning and fine-tuning techniques.
A multi-voice text-to-speech system that produces highly realistic prosody and intonation using autoregressive and diffusion decoders.
A low-code declarative framework for building custom LLMs, neural networks, and other AI models with YAML configurations.
A low-code declarative framework for building custom LLMs, neural networks, and other AI models with YAML configurations.
An open-source NLP framework for building and deploying deep learning dialog systems and chatbots with PyTorch and transformers.
A Python library that extends OpenAI's Whisper to provide accurate word-level timestamps and confidence scores for multilingual speech recognition.
State-of-the-art pre-trained transformer language models for protein sequences, enabling tasks like structure prediction and function annotation.
A method to steer topic and attributes of GPT-2 language models without fine-tuning, enabling controlled text generation.
An open-source study on neural question generation using transformers, providing simplified training and inference pipelines.
A PyTorch-based framework for training and validating models that produce high-quality embeddings for metric learning and retrieval tasks.
A model-agnostic method for generating high-precision rule-based explanations for black-box classifier predictions.
A pre-trained BERT model designed for DNA sequence analysis, enabling genome understanding tasks like classification and motif discovery.
A Google Colab notebook that transcribes YouTube videos using OpenAI's Whisper speech recognition model.
A command-line interface for blazingly fast audio transcription using optimized Whisper ASR models.
A BERT-based foundation model pretrained on large-scale scRNA-seq data for automated cell type annotation in single-cell analysis.
A collection of genomic language models for predicting variant effects and evolutionary constraints from DNA sequences.
An on-device AI teleprompter that listens to your conversations and suggests charismatic quotes in real-time.
A Python library that simplifies using, finetuning, and deploying state-of-the-art machine learning models for various AI tasks.
A T5-based model for bidirectional translation between molecular structures (SMILES) and natural language descriptions.
A conversational AI framework for editing small molecules, peptides, and proteins using retrieval-augmented generation and domain feedback.
A collection of pre-trained BERT, DistilBERT, ELECTRA, GPT-2, and ConvBERT models for multiple languages, including German, Italian, Turkish, and historic texts.
A GPT-2 model trained from scratch on password leaks for password modeling, generation, and strength estimation.
German language versions of GPT-2, trained on the CC-100 corpus and initialized from English GPT-2 weights.
A framework for evaluating German transformer language models using syntactic agreement tests.
A dynamic inference wrapper for Transformer language models that enables per-token layer skipping to reduce computational FLOPs.
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.