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Machine Learning Engineering Open Book
Official codebase used to develop Vision Transformer, SigLIP, MLP-Mixer, LiT and more.
[ACL 2024] An Easy-to-use Knowledge Editing Framework for LLMs.
A collection of learning resources for curious software engineers
Modeling, training, eval, and inference code for OLMo
A repository of links with advice related to grad school applications, research, phd etc
Fast and memory-efficient exact attention
ML Collections is a library of Python Collections designed for ML use cases.
The hub for EleutherAI's work on interpretability and learning dynamics
Erasing concepts from neural representations with provable guarantees
An efficient video loader for deep learning with smart shuffling that's super easy to digest
Code and models for NExT-GPT: Any-to-Any Multimodal Large Language Model
A collection of inspiring lists, manuals, cheatsheets, blogs, hacks, one-liners, cli/web tools and more.
Rigourous evaluation of LLM-synthesized code - NeurIPS 2023 & COLM 2024
Easily compute clip embeddings and build a clip retrieval system with them
Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
20 high-performance LLMs with recipes to pretrain, finetune and deploy at scale.
🤖 A PyTorch library of curated Transformer models and their composable components
[ICCV2023 Oral] Unmasked Teacher: Towards Training-Efficient Video Foundation Models
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
Efficient few-shot learning with Sentence Transformers
Leveraging BERT and c-TF-IDF to create easily interpretable topics.
Public repo for the NeurIPS 2023 paper "Unlimiformer: Long-Range Transformers with Unlimited Length Input"
QLoRA: Efficient Finetuning of Quantized LLMs
A curated list of data oriented design resources.
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities