Awesome-Chinese-LLM - 整理开源的中文大语言模型,以规模较小、可私有化部署、训练成本较低的模型为主,包括底座模型,垂直领域微调及应用,数据集与教程等。 LLM4Opt - Applying Large language models (LLMs) for diverse optimization tasks (Opt) is an emerging research area. This is a collection of referen...
15k Star的LLM应用开发圣经——awesome-llm-apps深度解析 * 戳上方蓝字“牛皮糖不吹牛”关注我 大家好,我是牛皮糖!这几天DeepSeek火爆了,学习LLM 应用也在GitHub 火爆了,这个项目在GitHub 一天新增1000+Stars。 作为AI领域最全面的LLM应用开发指南,这个项目三大杀手锏让你无法拒绝: 1️⃣全栈模型支持:覆盖从商业...
Awesome-LLM 🔥 Large Language Models(LLM) have taken theNLP communityAI communitythe Whole Worldby storm. Here is a curated list of papers about large language models, especially relating to ChatGPT. It also contains frameworks for LLM training, tools to deploy LLM, courses and tutorials about...
Awesome-Chinese-LLM 整理了开源的中文大模型相关资源,包括开源底座模型、垂直领域微调模型应用、数据集及教程等。目前,收录的资源已超过100个,涵盖了从小型到大型的多种模型,如ChatGLM、LLaMA、Baichuan、Qwe…
地址:https://github.com/ymcui/Chinese-LLaMA-Alpaca-2 简介:该项目将发布中文LLaMA-2 & Alpaca-2大语言模型,基于可商用的LLaMA-2进行二次开发。 Chinese-LlaMA2: 地址:https://github.com/michael-wzhu/Chinese-LlaMA2 简介:该项目基于可商用的LLaMA-2进行二次开发决定在次开展Llama 2的中文汉化工作,包括Ch...
https://github.com/wgwang/awesome-LLMs-In-China https://github.com/wgwang/awesome-open-foundation-models 大模型相关的Awesome系列包括: 大模型评测数据集:https://github.com/wgwang/awesome-LLM-benchmarks 中国大模型列表:https://github.com/wgwang/awesome-LLMs-In-China ...
Reasoning in Large Language Models: Papers and Resources, including Chain-of-Thought, Instruction-Tuning and Multimodality. - GitHub - kekewind/Awesome-LLM-Reasoning: Reasoning in Large Language Models: Papers and Resources, including Chain-of-Thought,
Awesome LLMs Datasets Summarize existing representative LLMs text datasets across five dimensions:Pre-training Corpora, Fine-tuning Instruction Datasets, Preference Datasets, Evaluation Datasets, and Traditional NLP Datasets. (Regular updates) New dataset sections have been added:Multi-modal Large Language ...
项目地址:https://github.com/RUCAIBox/awesome-llm-pretraining目录技术报告训练策略开源数据集数据方法一、技术报告技术报告的背后往往都是成百上千的算力资源作为支撑,因此很推荐仔细阅读优质开源技术报告。受篇幅所限,我们列举了一些近期经典的技术报告,更多的...
A curated list of Awesome-LLM-Ensemble papers for the survey "Harnessing Multiple Large Language Models: A Survey on LLM Ensemble" - junchenzhi/Awesome-LLM-Ensemble