A curated list of foundation models for vision and language tasks
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Updated
May 24, 2024
A curated list of foundation models for vision and language tasks
Fast inference engine for Transformer models
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.
An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites
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.
👨🎨 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.
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