18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
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Updated
May 13, 2024 - Jupyter Notebook
18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
🧑🏫 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, ... 🧠
👑 Easy-to-use and powerful NLP and LLM library with 🤗 Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including 🗂Text Classification, 🔍 Neural Search, ❓ Question Answering, ℹ️ Information Extraction, 📄 Document Intelligence, 💌 Sentiment Analysis etc.
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Unify Efficient Fine-Tuning of 100+ LLMs
CVPR 2024 论文和开源项目合集
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
Ongoing research training transformer models at scale
🔍 LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
A PyTorch-based Speech Toolkit
This repository contains demos I made with the Transformers library by HuggingFace.
Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, Baichuan, Mixtral, Gemma, etc.) on Intel CPU and GPU (e.g., local PC with iGPU, discrete GPU such as Arc, Flex and Max). A PyTorch LLM library that seamlessly integrates with llama.cpp, Ollama, HuggingFace, LangChain, LlamaIndex, DeepSpeed, vLLM, FastChat, etc.
Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
An implementation of model parallel autoregressive transformers on GPUs, based on the Megatron and DeepSpeed libraries
An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.
Providing enterprise-grade LLM-based development framework, tools, and fine-tuned models.
BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
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