A curated list of awesome LLM Inference-Time Self-Improvement (ITSI, pronounced "itsy") papers from our recent survey: A Survey on Large Language Model Inference-Time Self-Improvement.

Official github repo for TMMLU+, Large scale traditional chinese massive multitask language understanding

Official code for Wav2Seq

Cramming the training of a (BERT-type) language model into limited compute.

VaLM: Visually-augmented Language Modeling. ICLR 2023.

Implementation of ChatGPT RLHF (Reinforcement Learning with Human Feedback) on any generation model in huggingface's transformer (blommz-176B/bloom/gpt/bart/T5/MetaICL)

Textless (ASR-transcript free) Spoken Question Answering. The official release of NMSQA dataset and the implementation of "DUAL: Textless Spoken Question Answering with Speech Discrete Unit Adaptiv…

phoneme byt5

Code for the manim-generated scenes used in 3blue1brown videos

Toolkit for downloading and processing Google's AudioSet dataset.

Simple image captioning model

🏃 hosting nlp models in one line

🍳 NLPrep - dataset tool for many natural language processing task

🤖📇 handling multiple nlp task in one pipeline

Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr\"om Method (NeurIPS 2021)

Python API for reading and querying ARPA formatted language models.

Unofficial PyTorch implementation of Google's FNet: Mixing Tokens with Fourier Transforms. With checkpoints.

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…

⚡ Competitive Programming Library

A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

PyTorch package for the discrete VAE used for DALL·E.

Projects developed during the Spring 2017 Computational Audio course at Boston University.

PyTorch code for EMNLP 2020 Paper "Vokenization: Improving Language Understanding with Visual Supervision"

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

PyTorch code for EMNLP 2019 paper "LXMERT: Learning Cross-Modality Encoder Representations from Transformers".