🦜🔗 Build context-aware reasoning applications

A latent text-to-image diffusion model

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

QLoRA: Efficient Finetuning of Quantized LLMs

LAVIS - A One-stop Library for Language-Vision Intelligence

PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

Data augmentation for NLP

A Unified Library for Parameter-Efficient and Modular Transfer Learning

Code for "LoFTR: Detector-Free Local Feature Matching with Transformers", CVPR 2021, T-PAMI 2022

Code for Stanford CS224u

An automatic evaluator for instruction-following language models. Human-validated, high-quality, cheap, and fast.

Official code for "FeatUp: A Model-Agnostic Frameworkfor Features at Any Resolution" ICLR 2024

Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome

Using GPT to organize and access information, and generate questions. Long term goal is to make an agent-like research assistant.

[ICLR 2022] Official implementation of the paper "DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR"

BERT with SentencePiece for Japanese text.