Orchestrate Swarms of Agents From Any Framework Like OpenAI, Langchain, and Etc for Business Operation Automation. Join our Community: https://discord.gg/DbjBMJTSWD

Scikit-learn friendly library to interpret, and prompt-engineer text datasets using large language models.

A curated list of foundation models for vision and language tasks

An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites

Fast inference engine for Transformer models

Cerbrec Graphbook is the deep learning framework that brings visibility and intelligent guidance to researchers.

pytorch下基于transformer / LSTM模型的彩票预测

Implement, train, tune, and evaluate a transformer model for antibody classification with this step-by-step code.

Pre-training a Transformer from scratch.

[CVPR 2024] Code for our Paper "CFAT: Unleashing Triangular Windows for Image Super-resolution"

Final project for the Speaker Recognition course on Udemy, 机器之心, 深蓝学院 and 语音之家

solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning

This project offers a deeper exploration of tttzof351's "Simple Transformer TTS" codebase, enhanced with insights from Gemini Advanced, Google AI's language model.

Visualizing query-key interactions in language + vision transformers

Applying Transformer-based models to the imbalanced multi-label Reuters News Dataset text classification task.

Flops counter for convolutional networks in pytorch framework

Q&Arabic is an NLP framework that generates Arabic FAQs from a given material. The project uses deep learning models (BERT and T5) and includes a detailed report and brief presentation covering the system analysis, related work, and future plans.

Dataset of T1 model.

👨‍🎨 DDPM, and High-Resolution Image Synthesis with Latent Diffusion Models, papers implementation from scratch using pytorch.

Context-Aware Residual Transformer (CART) is a kiosk recommendation system (CART) that utilizes self-supervised learning techniques tailored to kiosks in an offline retail environment and developed by a collaboration between NS Lab @ CUK and IIP Lab @ Gachon University based on pure PyTorch backend.