Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

Ongoing research training transformer models at scale

Easy-to-use and powerful LLM and SLM library with awesome model zoo.

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.

Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.

A PyTorch-based Speech Toolkit

Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, DeepSeek, Mixtral, Gemma, Phi, MiniCPM, Qwen-VL, MiniCPM-V, etc.) on Intel XPU (e.g., local PC with iGPU and NPU, discrete GPU such as Arc, Flex and Max); seamlessly integrate with llama.cpp, Ollama, HuggingFace, LangChain, LlamaIndex, vLLM, DeepSpeed, Axolotl, etc.

An implementation of model parallel autoregressive transformers on GPUs, based on the Megatron and DeepSpeed libraries

RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.

An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.

Machine Learning Engineering Open Book

Leveraging BERT and c-TF-IDF to create easily interpretable topics.

BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)

An open-source framework for detecting, redacting, masking, and anonymizing sensitive data (PII) across text, images, and structured data. Supports NLP, pattern matching, and customizable pipelines.

An Easy-to-use, Scalable and High-performance RLHF Framework based on Ray (PPO & GRPO & REINFORCE++ & vLLM & Ray & Dynamic Sampling & Async Agentic RL)

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

Transformers for Information Retrieval, Text Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI