transformers

A Bottom-Up Instance Segmentation Strategy for segmenting document instances using Transformers

Implementation of OmniNet, Omnidirectional Representations from Transformers, in Pytorch

Build Semantic Search with S-BERT and Fine-tune your model in unsupervised way

Implementation of Mind Evolution, Evolving Deeper LLM Thinking, from Deepmind

Code for NOLA, an implementation of "nola: Compressing LoRA using Linear Combination of Random Basis"

OOD Generalization and Detection (ACL 2020)

TrAVis: Visualise BERT attention in your browser

🤗 최소한의 세팅으로 LM을 학습하기 위한 샘플코드

Pytorch reimplementation of Molecule Attention Transformer, which uses a transformer to tackle the graph-like structure of molecules

Lightweight multilingual language models for consumer hardware

[CVPR 2023] Official code repository for "How you feelin'? Learning Emotions and Mental States in Movie Scenes". https://arxiv.org/abs/2304.05634

Tutorial to pretrain & fine-tune a 🤗 Flax T5 model on a TPUv3-8 with GCP

Exploration into the proposed "Self Reasoning Tokens" by Felipe Bonetto

🤖📇 handling multiple nlp task in one pipeline

[NeurIPS 2025] PARCO: Parallel AutoRegressive Combinatorial Optimization

Speaker change detection using SincNet and an LSTM/Transformer

Korean version of GoEmotions Dataset 😍😢😱

Time series explainability via self-supervised model behavior consistency

EVE bot, a customer service chatbot to enhance virtual engagement for Twitter Apple Support

hummingbird is a lightweight, zero dependency runtime for massive open source Mixture of Experts (MoE) language models. It unifies SSD, RAM, and VRAM into a single intelligent memory hierarchy, enabling inference of models like GPT-OSS 120B, GLM, DeepSeek, Qwen, and more on consumer hardware