--- title: "Reading_groups vs LlamaFactory" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/crazyofapple-reading-groups-vs-hiyouga-llamafactory" tools: ["crazyofapple-reading-groups", "hiyouga-llamafactory"] --- # Reading_groups vs LlamaFactory *GraphCanon updated Jul 11, 2026* ## Verdict Pick Reading_groups if 用于跟踪、整理和学习大规模语言模型相关的文章、课程材料和实验演示，适用于希望了解最新技术进展、优化策略、应用案例以及深度分析的研究者。; pick LlamaFactory if llamaFactory is a sophisticated tool for fine-tuning numerous large language models and visual language models efficiently using various methods such as LoRA, QLoRA, RLHF, and quantization. [Reading_groups](https://github.com/crazyofapple/Reading_groups) reports 202 GitHub stars, 7 forks, and 0 open issues, last pushed Aug 8, 2023. [LlamaFactory](https://llamafactory.readthedocs.io) has 73k stars, 8.9k forks, and 1.1k open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [Reading_groups's repository](https://github.com/crazyofapple/Reading_groups) and [LlamaFactory's repository](https://github.com/hiyouga/LlamaFactory). | | [Reading_groups](/tools/crazyofapple-reading-groups.md) | [LlamaFactory](/tools/hiyouga-llamafactory.md) | | --- | --- | --- | | Tagline | 资源整理和追踪大规模预训练语言模型相关文章 | Unified Efficient Fine-Tuning of 100+ LLMs & VLMs | | Stars | 202 | 73,157 | | Forks | 7 | 8,937 | | Open issues | 0 | 1,067 | | Language | - | Python | | Adopt for | 用于跟踪、整理和学习大规模语言模型相关的文章、课程材料和实验演示，适用于希望了解最新技术进展、优化策略、应用案例以及深度分析的研究者。 | LlamaFactory is a sophisticated tool for fine-tuning numerous large language models and visual language models efficiently using various methods such as LoRA, QLoRA, RLHF, and quantization. | | Persona | - | - | | Runtime | - | - | | License | - | Apache-2.0 | | Categories | Developer Tools, Evaluation & Observability, LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Reading_groups](/tools/crazyofapple-reading-groups.md) | [LlamaFactory](/tools/hiyouga-llamafactory.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 1068d | 0d | | Open issues (now) | 0 | 1.1k | | Full report | [trust report](/tools/crazyofapple-reading-groups/trust.md) | [trust report](/tools/hiyouga-llamafactory/trust.md) | ## Decision facts: Reading_groups - **Adopt for:** 用于跟踪、整理和学习大规模语言模型相关的文章、课程材料和实验演示，适用于希望了解最新技术进展、优化策略、应用案例以及深度分析的研究者。 ## Decision facts: LlamaFactory - **Adopt for:** LlamaFactory is a sophisticated tool for fine-tuning numerous large language models and visual language models efficiently using various methods such as LoRA, QLoRA, RLHF, and quantization. ## Choose when ### Choose Reading_groups if… - Tags unique to Reading_groups: chatgpt, gpt-3, gpt-4, llm. - Also covers Developer Tools, Evaluation & Observability. - 您想深入理解特定的大规模预训练语言模型（如GPT-4）、其性能测试及其局限性时 ### Choose LlamaFactory if… - Tags unique to LlamaFactory: agent, ai, deepseek, fine-tuning. - When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA. - More GitHub stars (73k vs 202) - visibility, not fit. ## When NOT to use Reading_groups - 如果您主要关注软件层面的开发工具或特定框架的具体实现代码时。Reading_groups专注于论文资源和理论方向，而不是具体实现技巧 - 当您寻求快速入门基础NLP概念或者新手向教程支持时，该库更倾向于高级研究与前沿议题 - 需要深入对比分析S4等颠覆型架构细节，因为此仓库主要关注现有大规模预训练语言模型的演进步骤和技术迭代 ## When NOT to use LlamaFactory - When you are looking to fine-tune less popular or niche models that are not supported within the 100+ models covered by LlamaFactory. - If your project specifically requires custom fine-tuning methods not available in this repository, such as certain versions of PEFT (Parameter Efficient Fine-Tuning) techniques excluding LoRA and QLoa ## Common questions ### What is the difference between Reading_groups and LlamaFactory? Reading_groups: 资源整理和追踪大规模预训练语言模型相关文章. LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. See the comparison table for live GitHub stats and shared categories. ### When should I choose Reading_groups over LlamaFactory? Choose Reading_groups over LlamaFactory when Tags unique to Reading_groups: chatgpt, gpt-3, gpt-4, llm; Also covers Developer Tools, Evaluation & Observability; 您想深入理解特定的大规模预训练语言模型（如GPT-4）、其性能测试及其局限性时. ### When should I choose LlamaFactory over Reading_groups? Choose LlamaFactory over Reading_groups when Tags unique to LlamaFactory: agent, ai, deepseek, fine-tuning; When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA; More GitHub stars (73k vs 202) - visibility, not fit. ### When should I avoid Reading_groups? 如果您主要关注软件层面的开发工具或特定框架的具体实现代码时。Reading_groups专注于论文资源和理论方向，而不是具体实现技巧 当您寻求快速入门基础NLP概念或者新手向教程支持时，该库更倾向于高级研究与前沿议题 需要深入对比分析S4等颠覆型架构细节，因为此仓库主要关注现有大规模预训练语言模型的演进步骤和技术迭代 ### When should I avoid LlamaFactory? When you are looking to fine-tune less popular or niche models that are not supported within the 100+ models covered by LlamaFactory. If your project specifically requires custom fine-tuning methods not available in this repository, such as certain versions of PEFT (Parameter Efficient Fine-Tuning) techniques excluding LoRA and QLoa ### Is Reading_groups or LlamaFactory more popular on GitHub? LlamaFactory has more GitHub stars (73,157 vs 202). Stars measure visibility, not whether either tool fits your constraints. ### Are Reading_groups and LlamaFactory open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to Reading_groups or LlamaFactory? GraphCanon lists graph-backed alternatives at [Reading_groups alternatives](/tools/crazyofapple-reading-groups/alternatives) and [LlamaFactory alternatives](/tools/hiyouga-llamafactory/alternatives) ([Reading_groups markdown twin](/tools/crazyofapple-reading-groups/alternatives.md), [LlamaFactory markdown twin](/tools/hiyouga-llamafactory/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/crazyofapple-reading-groups-vs-hiyouga-llamafactory.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Reading_groups or LlamaFactory? Reading_groups: Dormant. LlamaFactory: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for Reading_groups and LlamaFactory? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Reading_groups trust report](/tools/crazyofapple-reading-groups/trust); [LlamaFactory trust report](/tools/hiyouga-llamafactory/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=crazyofapple-reading-groups`](/api/graphcanon/graph?tool=crazyofapple-reading-groups) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_