Stars
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
A cross-platform ChatGPT/Gemini UI (Web / PWA / Linux / Win / MacOS). 一键拥有你自己的跨平台 ChatGPT/Gemini 应用。
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
Finetune Llama 3.2, Mistral, Phi, Qwen 2.5 & Gemma LLMs 2-5x faster with 80% less memory
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
SuperCLUE: 中文通用大模型综合性基准 | A Benchmark for Foundation Models in Chinese
Resume builder based on markdown syntax（在线简历制作工具 https://codecv.top）
NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN framework
ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
Acceptance rates for the major AI conferences
LSGNN: Towards General Graph Neural Network in Node Classification by Local Similarity
This list of writing prompts covers a range of topics and tasks, including brainstorming research ideas, improving language and style, conducting literature reviews, and developing research plans.
This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs", which is accepted to ICLR 2023.
Papers about Graph Contrastive Learning and Graph Self-supervised Learning on Graphs with Heterophily
A curated list of Heterophilous Graph Self-Supervised Learning papers.
This repository contains the resources on graph neural network (GNN) considering heterophily.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Use ChatGPT to summarize the arXiv papers. 全流程加速科研，利用chatgpt进行论文全文总结+专业翻译+润色+审稿+审稿回复
Code for the AAAI 2023 paper: "Global-Local Characteristic Excited Cross-Modal Attacks from Images to Video" (accepted).
A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?
XNOR-Net with binary conv2d kernels with XNOR GEMM op, support both CPU and GPU.
XNOR-Net, with binary gemm and binary conv2d kernels, support both CPU and GPU.