T

transformers

https://github.com/lucidrains/x-transformers A simple but complete full-attention transformer with a set of promising experimental features from various papers

🔧🔗https://github.com/hiyouga/LLaMA-Factory Unified Efficient Fine-Tuning of 100+ LLMs (ACL 2024)

https://github.com/lucidrains/vit-pytorch mplementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

https://github.com/huggingface/swift-transformers Swift Package to implement a transformers-like API in Swift

🔧🔗https://github.com/lucidrains/pi-zero-pytorch

Implementation of π₀, the robotic foundation model architecture proposed by Physical Intelligence

🔧🔗https://github.com/speechbrain/speechbrain A PyTorch-based Speech Toolkit

🔧🔗https://github.com/lucidrains/transfusion-pytorch

Pytorch implementation of Transfusion, "Predict the Next Token and Diffuse Images with One Multi-Modal Model", from MetaAI

LLMs from scratch

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step 🔧🔗https://github.com/rasbt/LLMs-from-scratch

🔧🔗https://github.com/FoundationVision/VAR [NeurIPS 2024 Oral][GPT beats diffusion🔥] [scaling laws in visual generation📈] Official impl. of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction". An ultra-simple, user-friendly yet state-of-the-art codebase for autoregressive image generation!

🔧🔗https://github.com/forhaoliu/ringattention

Transformers with Arbitrarily Large Context

🔧🔗https://github.com/codelion/adaptive-classifier A flexible, adaptive classification system for dynamic text classification

🔧🔗https://github.com/lucidrains/alphafold3-pytorch Implementation of Alphafold 3 from Google Deepmind in Pytorch

https://github.com/InternLM/lagent A lightweight framework for building LLM-based agents

CSTR

🔧🔗https://github.com/manycore-research/cstr [arXiv prepreint] Deep Learning Assisted Optimization for 3D Reconstruction from Single 2D Line Drawings

🔧🔗https://github.com/openai/transformer-debugger/ Transformer Debugger (TDB) is a tool developed by OpenAI's Superalignment team with the goal of supporting investigations into specific behaviors of small language models. The tool combines automated interpretability techniques with sparse autoencoders.

🔧🔗https://github.com/takara-ai/SwarmFormer

A pytorch implementation of SwarmFormer for text classification.

🔧🔗https://github.com/lucidrains/q-transformer Implementation of Q-Transformer, Scalable Offline Reinforcement Learning via Autoregressive Q-Functions, out of Google Deepmind

https://github.com/lucidrains/soundstorm-pytorch Implementation of SoundStorm, Efficient Parallel Audio Generation from Google Deepmind, in Pytorch

https://github.com/lucidrains/audiolm-pytorch Implementation of AudioLM, a SOTA Language Modeling Approach to Audio Generation out of Google Research, in Pytorch

https://github.com/lucidrains/magvit2-pytorch Implementation of MagViT2 Tokenizer in Pytorch