使用预训练语言模型BERT做中文NER

ImageNet pre-trained models with batch normalization for the Caffe framework

使用预训练语言模型ALBERT做中文NER

Adapting Meta AI's Segment Anything to Downstream Tasks with Adapters and Prompts

Scale LLM Engine public repository

Fine-tune SAM (Segment Anything Model) for computer vision tasks such as semantic segmentation, matting, detection ... in specific scenarios

Fine-tuning code for CLIP models

Use FastSpeech2 and HiFi-GAN to easily perform end-to-end Korean speech synthesis.

[SOTA] [92% acc] 786M-8k-44L-32H multi-instrumental music transformer with true full MIDI instruments range, efficient encoding, octo-velocity and outro tokens

TensorFlow Implementation of Manifold Regularized Convolutional Neural Networks.

Sparse Autoencoders (SAE) vs CLIP fine-tuning fun.

Vision Transformers Needs Registers. And Gated MLPs. And +20M params. Tiny modality gap ensues!

A Tensorflow implementation of YOLOv3.

A Novel Optimized ResNet-SD Model for Brain Tumor Classification Using Stochastic Depth and Metaheuristic Optimization

Exam Char Key — 面向古代汉语学习的AI智能辅助平台，融合阿里云Qwen模型，提供精准的汉字释义，助力高效学习与研究。现代前后端技术栈，支持容器化部署与学习进度管理。

This repository contains a PyTorch implementation of a Convolutional Neural Network (CNN) for classifying the MNIST dataset. The project explores different fine-tuning techniques, including LoRA (Low-Rank Adaptation), DoRA (Dynamic Low-Rank Adaptation), and QLoRA (Quantized Low-Rank Adaptation), to improve model performance and efficiency.

grocery store image classification with Keras

Vision Transformers Needs Registers. And Gated MLPs. And +20M params. Tiny modality gap ensues!

This repository contains the source code for the first and the second task of DeftEval 2020 competition, used by the University Politehnica of Bucharest (UPB) team to train and evaluate the models.

This application aims to classify real life photos of a cube game using deep learning algorithms based on a fine-tuned ResNet50. The script is deployed and accessible through a REST-ful web service.