--- title: "LlamaFactory vs LLMs-Finetuning-Safety" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hiyouga-llamafactory-vs-llm-tuning-safety-llms-finetuning-safety" tools: ["hiyouga-llamafactory", "llm-tuning-safety-llms-finetuning-safety"] --- # LlamaFactory vs LLMs-Finetuning-Safety *GraphCanon updated Jul 11, 2026* ## Verdict Pick LlamaFactory when license: LlamaFactory is Apache-2.0, LLMs-Finetuning-Safety is MIT; pick LLMs-Finetuning-Safety when license: LLMs-Finetuning-Safety is MIT, LlamaFactory is Apache-2.0. [LlamaFactory](https://llamafactory.readthedocs.io) reports 73k GitHub stars, 8.9k forks, and 1.1k open issues, last pushed Jul 10, 2026. [LLMs-Finetuning-Safety](https://llm-tuning-safety.github.io/) has 355 stars, 38 forks, and 3 open issues, last pushed Feb 23, 2024. Figures are from public GitHub metadata via [LlamaFactory's repository](https://github.com/hiyouga/LlamaFactory) and [LLMs-Finetuning-Safety's repository](https://github.com/LLM-Tuning-Safety/LLMs-Finetuning-Safety). | | [LlamaFactory](/tools/hiyouga-llamafactory.md) | [LLMs-Finetuning-Safety](/tools/llm-tuning-safety-llms-finetuning-safety.md) | | --- | --- | --- | | Tagline | Unified Efficient Fine-Tuning of 100+ LLMs & VLMs | We jailbreak GPT-3.5 Turbo’s safety guardrails by fine-tuning it on only 10 adversarially designed examples, at a cost of less than $0.20 via OpenAI’s APIs. | | Stars | 73,157 | 355 | | Forks | 8,937 | 38 | | Open issues | 1,067 | 3 | | Language | Python | 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 | Apache-2.0 | MIT | | Categories | LLM Frameworks, Model Training | Evaluation & Observability, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [LlamaFactory](/tools/hiyouga-llamafactory.md) | [LLMs-Finetuning-Safety](/tools/llm-tuning-safety-llms-finetuning-safety.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 869d | | Open issues (now) | 1.1k | 3 | | Full report | [trust report](/tools/hiyouga-llamafactory/trust.md) | [trust report](/tools/llm-tuning-safety-llms-finetuning-safety/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 LlamaFactory if… - License: LlamaFactory is Apache-2.0, LLMs-Finetuning-Safety 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 LLMs-Finetuning-Safety if… - License: LLMs-Finetuning-Safety is MIT, LlamaFactory is Apache-2.0. - Tags unique to LLMs-Finetuning-Safety: alignment, llm, llm-finetuning, python. - Also covers Evaluation & Observability. ## 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 LLMs-Finetuning-Safety - Last GitHub push was 869 days ago (dormant maintenance, Feb 23, 2024). Validate activity before betting a new project on LLMs-Finetuning-Safety. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. - 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. ## Common questions ### What is the difference between LlamaFactory and LLMs-Finetuning-Safety? LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. LLMs-Finetuning-Safety: We jailbreak GPT-3.5 Turbo’s safety guardrails by fine-tuning it on only 10 adversarially designed examples, at a cost of less than $0.20 via OpenAI’s APIs.. See the comparison table for live GitHub stats and shared categories. ### When should I choose LlamaFactory over LLMs-Finetuning-Safety? Choose LlamaFactory over LLMs-Finetuning-Safety when License: LlamaFactory is Apache-2.0, LLMs-Finetuning-Safety 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 LLMs-Finetuning-Safety over LlamaFactory? Choose LLMs-Finetuning-Safety over LlamaFactory when License: LLMs-Finetuning-Safety is MIT, LlamaFactory is Apache-2.0; Tags unique to LLMs-Finetuning-Safety: alignment, llm, llm-finetuning, python; Also covers Evaluation & Observability. ### 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 LLMs-Finetuning-Safety? Last GitHub push was 869 days ago (dormant maintenance, Feb 23, 2024). Validate activity before betting a new project on LLMs-Finetuning-Safety. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. 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. ### Is LlamaFactory or LLMs-Finetuning-Safety more popular on GitHub? LlamaFactory has more GitHub stars (73,157 vs 355). Stars measure visibility, not whether either tool fits your constraints. ### Are LlamaFactory and LLMs-Finetuning-Safety open source? Yes - both are open-source projects on GitHub (LlamaFactory: Apache-2.0, LLMs-Finetuning-Safety: MIT). ### Where can I find alternatives to LlamaFactory or LLMs-Finetuning-Safety? GraphCanon lists graph-backed alternatives at [LlamaFactory alternatives](/tools/hiyouga-llamafactory/alternatives) and [LLMs-Finetuning-Safety alternatives](/tools/llm-tuning-safety-llms-finetuning-safety/alternatives) ([LlamaFactory markdown twin](/tools/hiyouga-llamafactory/alternatives.md), [LLMs-Finetuning-Safety markdown twin](/tools/llm-tuning-safety-llms-finetuning-safety/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-llm-tuning-safety-llms-finetuning-safety.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, LlamaFactory or LLMs-Finetuning-Safety? LlamaFactory: Very active. LLMs-Finetuning-Safety: Dormant. 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 LLMs-Finetuning-Safety? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LlamaFactory trust report](/tools/hiyouga-llamafactory/trust); [LLMs-Finetuning-Safety trust report](/tools/llm-tuning-safety-llms-finetuning-safety/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/_