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Tsinghua University
- Beijing
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12:14
(UTC +08:00) - https://www.tsinghua.edu.cn/
- https://orcid.org/0000-0003-3106-320X
Highlights
- Pro
Stars
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
Free, open source crypto trading bot
A curated list of awesome skills, hooks, slash-commands, agent orchestrators, applications, and plugins for Claude Code by Anthropic
Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, i…
ChatGLM-6B: An Open Bilingual Dialogue Language Model | 开源双语对话语言模型
An Open Phone Agent Model & Framework. Unlocking the AI Phone for Everyone
ChatGLM3 series: Open Bilingual Chat LLMs | 开源双语对话语言模型
GLM-130B: An Open Bilingual Pre-Trained Model (ICLR 2023)
Implementation of the LLaMA language model based on nanoGPT. Supports flash attention, Int8 and GPTQ 4bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.
slime is an LLM post-training framework for RL Scaling.
GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models
Chinese and English multimodal conversational language model | 多模态中英双语对话语言模型
[NeurIPS 2024] OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments
[NeurIPS 2023] ImageReward: Learning and Evaluating Human Preferences for Text-to-image Generation
WebGLM: An Efficient Web-enhanced Question Answering System (KDD 2023)
SwissArmyTransformer is a flexible and powerful library to develop your own Transformer variants.
GLM-ASR-Nano: A robust, open-source speech recognition model with 1.5B parameters
Building Open LLM Web Agents with Self-Evolving Online Curriculum RL
Scaling Agentic Reinforcement Learning with a Multi-Turn, Multi-Task Framework
hanyullai / OSWorld
Forked from xlang-ai/OSWorld[NeurIPS 2024] OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments
HF_Trainer is a Huggingface-based framework for training LLMs, supporting pre-training, fine-tuning, reward modeling, and DPO training.


