--- title: "multilingual-safety-for-LLMs vs LlamaFactory" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/damo-nlp-sg-multilingual-safety-for-llms-vs-hiyouga-llamafactory" tools: ["damo-nlp-sg-multilingual-safety-for-llms", "hiyouga-llamafactory"] --- # multilingual-safety-for-LLMs vs LlamaFactory *GraphCanon updated Jul 11, 2026* ## Verdict Pick multilingual-safety-for-LLMs when license: multilingual-safety-for-LLMs is MIT, LlamaFactory is Apache-2.0; pick LlamaFactory when license: LlamaFactory is Apache-2.0, multilingual-safety-for-LLMs is MIT. [multilingual-safety-for-LLMs](https://github.com/DAMO-NLP-SG/multilingual-safety-for-LLMs) reports 105 GitHub stars, 8 forks, and 0 open issues, last pushed Mar 7, 2024. [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 [multilingual-safety-for-LLMs's repository](https://github.com/DAMO-NLP-SG/multilingual-safety-for-LLMs) and [LlamaFactory's repository](https://github.com/hiyouga/LlamaFactory). | | [multilingual-safety-for-LLMs](/tools/damo-nlp-sg-multilingual-safety-for-llms.md) | [LlamaFactory](/tools/hiyouga-llamafactory.md) | | --- | --- | --- | | Tagline | [ICLR 2024]Data for "Multilingual Jailbreak Challenges in Large Language Models" | Unified Efficient Fine-Tuning of 100+ LLMs & VLMs | | Stars | 105 | 73,157 | | Forks | 8 | 8,937 | | Open issues | 0 | 1,067 | | 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. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Vector Databases, LLM Frameworks, Model Training | Model Training, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [multilingual-safety-for-LLMs](/tools/damo-nlp-sg-multilingual-safety-for-llms.md) | [LlamaFactory](/tools/hiyouga-llamafactory.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 856d | 0d | | Open issues (now) | 0 | 1.1k | | Owner type | Organization | User | | Full report | [trust report](/tools/damo-nlp-sg-multilingual-safety-for-llms/trust.md) | [trust report](/tools/hiyouga-llamafactory/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. ## Choose when ### Choose multilingual-safety-for-LLMs if… - License: multilingual-safety-for-LLMs is MIT, LlamaFactory is Apache-2.0. - Tags unique to multilingual-safety-for-LLMs: jailbreak, llm, multilingual, safety. - Also covers Vector Databases. ### Choose LlamaFactory if… - License: LlamaFactory is Apache-2.0, multilingual-safety-for-LLMs is MIT. - Tags unique to LlamaFactory: gemma, fine-tuning, deepseek, ai. - When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA. ## When NOT to use multilingual-safety-for-LLMs - Last GitHub push was 857 days ago (dormant maintenance, Mar 7, 2024). Validate activity before betting a new project on multilingual-safety-for-LLMs. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ## 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 multilingual-safety-for-LLMs and LlamaFactory? multilingual-safety-for-LLMs: [ICLR 2024]Data for "Multilingual Jailbreak Challenges in Large Language Models". LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. See the comparison table for live GitHub stats and shared categories. ### When should I choose multilingual-safety-for-LLMs over LlamaFactory? Choose multilingual-safety-for-LLMs over LlamaFactory when License: multilingual-safety-for-LLMs is MIT, LlamaFactory is Apache-2.0; Tags unique to multilingual-safety-for-LLMs: jailbreak, llm, multilingual, safety; Also covers Vector Databases. ### When should I choose LlamaFactory over multilingual-safety-for-LLMs? Choose LlamaFactory over multilingual-safety-for-LLMs when License: LlamaFactory is Apache-2.0, multilingual-safety-for-LLMs is MIT; Tags unique to LlamaFactory: gemma, fine-tuning, deepseek, ai; When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA. ### When should I avoid multilingual-safety-for-LLMs? Last GitHub push was 857 days ago (dormant maintenance, Mar 7, 2024). Validate activity before betting a new project on multilingual-safety-for-LLMs. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### 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 multilingual-safety-for-LLMs or LlamaFactory more popular on GitHub? LlamaFactory has more GitHub stars (73,157 vs 105). Stars measure visibility, not whether either tool fits your constraints. ### Are multilingual-safety-for-LLMs and LlamaFactory open source? Yes - both are open-source projects on GitHub (multilingual-safety-for-LLMs: MIT, LlamaFactory: Apache-2.0). ### Where can I find alternatives to multilingual-safety-for-LLMs or LlamaFactory? GraphCanon lists graph-backed alternatives at [multilingual-safety-for-LLMs alternatives](/tools/damo-nlp-sg-multilingual-safety-for-llms/alternatives) and [LlamaFactory alternatives](/tools/hiyouga-llamafactory/alternatives) ([multilingual-safety-for-LLMs markdown twin](/tools/damo-nlp-sg-multilingual-safety-for-llms/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/damo-nlp-sg-multilingual-safety-for-llms-vs-hiyouga-llamafactory.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, multilingual-safety-for-LLMs or LlamaFactory? multilingual-safety-for-LLMs: 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 multilingual-safety-for-LLMs and LlamaFactory? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [multilingual-safety-for-LLMs trust report](/tools/damo-nlp-sg-multilingual-safety-for-llms/trust); [LlamaFactory trust report](/tools/hiyouga-llamafactory/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=damo-nlp-sg-multilingual-safety-for-llms`](/api/graphcanon/graph?tool=damo-nlp-sg-multilingual-safety-for-llms) - 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/_