--- title: "LlamaFactory vs KnowledgeEditingPapers" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hiyouga-llamafactory-vs-zjunlp-knowledgeeditingpapers" tools: ["hiyouga-llamafactory", "zjunlp-knowledgeeditingpapers"] --- # LlamaFactory vs KnowledgeEditingPapers *GraphCanon updated Jul 12, 2026* ## Verdict 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; pick KnowledgeEditingPapers if a specialized collection of foundational papers and reports that delve into the editing and manipulation of knowledge within large language models, making it a valuable resource for researchers. [LlamaFactory](https://llamafactory.readthedocs.io) reports 73k GitHub stars, 8.9k forks, and 1.1k open issues, last pushed Jul 10, 2026. [KnowledgeEditingPapers](https://github.com/zjunlp/KnowledgeEditingPapers) has 1.2k stars, 79 forks, and 0 open issues, last pushed Jun 25, 2026. Figures are from public GitHub metadata via [LlamaFactory's repository](https://github.com/hiyouga/LlamaFactory) and [KnowledgeEditingPapers's repository](https://github.com/zjunlp/KnowledgeEditingPapers). | | [LlamaFactory](/tools/hiyouga-llamafactory.md) | [KnowledgeEditingPapers](/tools/zjunlp-knowledgeeditingpapers.md) | | --- | --- | --- | | Tagline | Unified Efficient Fine-Tuning of 100+ LLMs & VLMs | Must-read Papers on Knowledge Editing for Large Language Models | | Stars | 73,157 | 1,235 | | Forks | 8,937 | 79 | | Open issues | 1,067 | 0 | | Language | Python | - | | 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. | A specialized collection of foundational papers and reports that delve into the editing and manipulation of knowledge within large language models, making it a valuable resource for researchers looking to understand and斧 | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [LlamaFactory](/tools/hiyouga-llamafactory.md) | [KnowledgeEditingPapers](/tools/zjunlp-knowledgeeditingpapers.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 0d | 16d | | Open issues (now) | 1.1k | 0 | | Owner type | User | Organization | | Full report | [trust report](/tools/hiyouga-llamafactory/trust.md) | [trust report](/tools/zjunlp-knowledgeeditingpapers/trust.md) | ## 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. ## Decision facts: KnowledgeEditingPapers - **Hosting:** unknown - **Adopt for:** A specialized collection of foundational papers and reports that delve into the editing and manipulation of knowledge within large language models, making it a valuable resource for researchers looking to understand and斧 - **License detail:** MIT ## Choose when ### Choose LlamaFactory if… - License: LlamaFactory is Apache-2.0, KnowledgeEditingPapers is MIT. - 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. ### Choose KnowledgeEditingPapers if… - License: KnowledgeEditingPapers is MIT, LlamaFactory is Apache-2.0. - Tags unique to KnowledgeEditingPapers: knowledge-editing, model-editing, natural-language-processing, pre-trained-language-models. - You are specifically interested in recent advancements in knowledge editing techniques for large language models. ## 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 ## When NOT to use KnowledgeEditingPapers - You are looking for a broad overview of machine learning or AI in general, as this repository focuses narrowly on knowledge editing within large language models. - If you seek practical tooling or implementation guidance rather than theoretical insights and review papers. - Your focus is more on data preprocessing or model training techniques unrelated to the specific modification of knowledge mechanisms in LLMs. ## Common questions ### What is the difference between LlamaFactory and KnowledgeEditingPapers? LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. KnowledgeEditingPapers: Must-read Papers on Knowledge Editing for Large Language Models. See the comparison table for live GitHub stats and shared categories. ### When should I choose LlamaFactory over KnowledgeEditingPapers? Choose LlamaFactory over KnowledgeEditingPapers when License: LlamaFactory is Apache-2.0, KnowledgeEditingPapers is MIT; 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. ### When should I choose KnowledgeEditingPapers over LlamaFactory? Choose KnowledgeEditingPapers over LlamaFactory when License: KnowledgeEditingPapers is MIT, LlamaFactory is Apache-2.0; Tags unique to KnowledgeEditingPapers: knowledge-editing, model-editing, natural-language-processing, pre-trained-language-models; You are specifically interested in recent advancements in knowledge editing techniques for large language models. ### 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 ### When should I avoid KnowledgeEditingPapers? You are looking for a broad overview of machine learning or AI in general, as this repository focuses narrowly on knowledge editing within large language models. If you seek practical tooling or implementation guidance rather than theoretical insights and review papers. Your focus is more on data preprocessing or model training techniques unrelated to the specific modification of knowledge mechanisms in LLMs. ### Is LlamaFactory or KnowledgeEditingPapers more popular on GitHub? LlamaFactory has more GitHub stars (73,157 vs 1,235). Stars measure visibility, not whether either tool fits your constraints. ### Are LlamaFactory and KnowledgeEditingPapers open source? Yes - both are open-source projects on GitHub (LlamaFactory: Apache-2.0, KnowledgeEditingPapers: MIT). ### Where can I find alternatives to LlamaFactory or KnowledgeEditingPapers? GraphCanon lists graph-backed alternatives at [LlamaFactory alternatives](/tools/hiyouga-llamafactory/alternatives) and [KnowledgeEditingPapers alternatives](/tools/zjunlp-knowledgeeditingpapers/alternatives) ([LlamaFactory markdown twin](/tools/hiyouga-llamafactory/alternatives.md), [KnowledgeEditingPapers markdown twin](/tools/zjunlp-knowledgeeditingpapers/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/hiyouga-llamafactory-vs-zjunlp-knowledgeeditingpapers.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, LlamaFactory or KnowledgeEditingPapers? LlamaFactory: Very active. KnowledgeEditingPapers: 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 LlamaFactory and KnowledgeEditingPapers? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LlamaFactory trust report](/tools/hiyouga-llamafactory/trust); [KnowledgeEditingPapers trust report](/tools/zjunlp-knowledgeeditingpapers/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=hiyouga-llamafactory`](/api/graphcanon/graph?tool=hiyouga-llamafactory) - 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/_