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A high-throughput and memory-efficient inference and serving engine for LLMs
Fully open reproduction of DeepSeek-R1
Train transformer language models with reinforcement learning.
verl: Volcano Engine Reinforcement Learning for LLMs
Qwen2.5 is the large language model series developed by Qwen team, Alibaba Cloud.
YaRN: Efficient Context Window Extension of Large Language Models
GLM-4 series: Open Multilingual Multimodal Chat LMs | 开源多语言多模态对话模型
Pytorch Code for NeurIPS 2023 Paper---Public Opinion Field Effect Fusion in Representation Learning for Trending Topics Diffusion.
📰 Must-read papers and blogs on LLM based Long Context Modeling 🔥
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
Daily updated LLM papers. 每日更新 LLM 相关的论文，欢迎订阅 👏 喜欢的话动动你的小手 🌟 一个
ChatGLM-6B: An Open Bilingual Dialogue Language Model | 开源双语对话语言模型
🦜🔗 Build context-aware reasoning applications
本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）
Pytorch Code for ICDM 2023 Paper---Hierarchical Label Inference Incorporating Attribute Semantics in Attributed Networks.
ki-ljl / LINE
Forked from FrederickGeek8/LINELINE: Large-scale Information Network Embedding in PyTorch
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06
Some GNNs are implemented using PyG for link prediction tasks, including: GCN, GraphSAGE, GAT, Node2Vec、RGCN、HGT and HAN, which will continue to be updated in the future.
Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
⏰ Collaboratively track deadlines of conferences recommended by CCF (Website, Python Cli, Wechat Applet) / If you find it useful, please star this project, thanks~
A simple and extensible library to create Bayesian Neural Network layers on PyTorch.
Benchmark datasets, data loaders, and evaluators for graph machine learning
Some GNNs are implemented using PyG for node classification tasks, including: GCN, GraphSAGE, SGC, GAT, R-GCN and HAN (Heterogeneous Graph Attention Network), which will continue to be updated in t…
Must-read papers on graph neural networks (GNN)
Repository containing notebooks of my posts on Medium
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.