Comparison
multilingual-safety-for-LLMs vs LLMs-Finetuning-Safety
Verdict
Pick multilingual-safety-for-LLMs if data for studying multilingual jailbreak safety in LLMs, including nine non-English languages categorized by resource availability; pick LLMs-Finetuning-Safety if lLMs-Finetuning-Safety demonstrates the safety risks associated with fine-tuning GPT-3.5 Turbo using few adversarially designed examples.
Markdown twin · multilingual-safety-for-LLMs alternatives · LLMs-Finetuning-Safety alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | multilingual-safety-for-LLMs | LLMs-Finetuning-Safety |
|---|---|---|
| Maintenance | Dormant (880d since push) As of 2w · github_public_v1 | Dormant (893d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Personal account As of 2w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- multilingual-safety-for-LLMs
- Data for Multilingual Jailbreak Challenges in Large Language Models
- LLMs-Finetuning-Safety
- Demonstrates safety risks in fine-tuning GPT-3.5 Turbo with adversarial examples
Stars
- multilingual-safety-for-LLMs
- 107
- LLMs-Finetuning-Safety
- 358
Forks
- multilingual-safety-for-LLMs
- 8
- LLMs-Finetuning-Safety
- 38
Open issues
- multilingual-safety-for-LLMs
- 0
- LLMs-Finetuning-Safety
- 3
Language
- multilingual-safety-for-LLMs
- -
- LLMs-Finetuning-Safety
- Python
Adopt for
- multilingual-safety-for-LLMs
- Data for studying multilingual jailbreak safety in LLMs, including nine non-English languages categorized by resource availability.
- LLMs-Finetuning-Safety
- LLMs-Finetuning-Safety demonstrates the safety risks associated with fine-tuning GPT-3.5 Turbo using few adversarially designed examples.
Persona
- multilingual-safety-for-LLMs
- -
- LLMs-Finetuning-Safety
- -
Runtime
- multilingual-safety-for-LLMs
- -
- LLMs-Finetuning-Safety
- -
License
- multilingual-safety-for-LLMs
- MIT
- LLMs-Finetuning-Safety
- MIT
Last pushed
- multilingual-safety-for-LLMs
- Mar 7, 2024
- LLMs-Finetuning-Safety
- Feb 23, 2024
Categories
- multilingual-safety-for-LLMs
- Evaluation & Observability, Model Training
- LLMs-Finetuning-Safety
- Evaluation & Observability, Model Training
Trust and health
Days since push
- multilingual-safety-for-LLMs
- 880d
- LLMs-Finetuning-Safety
- 893d
Open issues (now)
- multilingual-safety-for-LLMs
- 0
- LLMs-Finetuning-Safety
- 3
Owner type
- multilingual-safety-for-LLMs
- Organization
- LLMs-Finetuning-Safety
- User
Full report
- multilingual-safety-for-LLMs
- Trust report
- LLMs-Finetuning-Safety
- Trust report
Choose multilingual-safety-for-LLMs if…
- Tags unique to multilingual-safety-for-LLMs: jailbreak, multilingual, safety.
- When evaluating the robustness of large language models against malicious prompts in multiple languages.
- More recently updated (last pushed Mar 7, 2024).
When NOT to use multilingual-safety-for-LLMs
- If solely focused on English-language security analysis, as this dataset emphasizes non-English prompts.
- When the target audience for your LLM is limited to high-resource language speakers only.
Choose LLMs-Finetuning-Safety if…
- Pricing: Open-source under the MIT license; free to use and modify. OpenAI API usage cost applies, but this repository demonstrates effects at less than $0.20..
- Tags unique to LLMs-Finetuning-Safety: adversarial training, alignment, llm-finetuning, model safety.
- When evaluating the risk of compromised safety in language models after fine-tuning them on small, carefully crafted datasets.
When NOT to use LLMs-Finetuning-Safety
- When generalizing safety risks to other large language models that have different underlying architectures or safeguard mechanisms than GPT-3.5 Turbo.
- If intending to use this tool as a method of fine-tuning any model for enhancing its performance on specific tasks, given it is designed for illustrating risk rather than improving capabilities.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (DAMO-NLP-SG/multilingual-safety-for-LLMs) · observed Aug 5, 2026
- GitHub forks (DAMO-NLP-SG/multilingual-safety-for-LLMs) · observed Aug 5, 2026
- Last push (DAMO-NLP-SG/multilingual-safety-for-LLMs) · observed Mar 7, 2024
- License file (MIT) · observed Aug 5, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (LLM-Tuning-Safety/LLMs-Finetuning-Safety) · observed Aug 5, 2026
- GitHub forks (LLM-Tuning-Safety/LLMs-Finetuning-Safety) · observed Aug 5, 2026
- Last push (LLM-Tuning-Safety/LLMs-Finetuning-Safety) · observed Feb 23, 2024
- License file (MIT) · observed Aug 5, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: multilingual-safety-for-LLMs 107 · LLMs-Finetuning-Safety 358 (synced Aug 5, 2026).
Common questions
- What is the difference between multilingual-safety-for-LLMs and LLMs-Finetuning-Safety?
- multilingual-safety-for-LLMs: Data for Multilingual Jailbreak Challenges in Large Language Models. LLMs-Finetuning-Safety: Demonstrates safety risks in fine-tuning GPT-3.5 Turbo with adversarial examples. See the comparison table for live GitHub stats and shared categories.
- When should I choose multilingual-safety-for-LLMs over LLMs-Finetuning-Safety?
- Choose multilingual-safety-for-LLMs over LLMs-Finetuning-Safety when Tags unique to multilingual-safety-for-LLMs: jailbreak, multilingual, safety; When evaluating the robustness of large language models against malicious prompts in multiple languages; More recently updated (last pushed Mar 7, 2024).
- When should I choose LLMs-Finetuning-Safety over multilingual-safety-for-LLMs?
- Choose LLMs-Finetuning-Safety over multilingual-safety-for-LLMs when Pricing: Open-source under the MIT license; free to use and modify. OpenAI API usage cost applies, but this repository demonstrates effects at less than $0.20.; Tags unique to LLMs-Finetuning-Safety: adversarial training, alignment, llm-finetuning, model safety; When evaluating the risk of compromised safety in language models after fine-tuning them on small, carefully crafted datasets.
- When should I avoid multilingual-safety-for-LLMs?
- If solely focused on English-language security analysis, as this dataset emphasizes non-English prompts. When the target audience for your LLM is limited to high-resource language speakers only.
- When should I avoid LLMs-Finetuning-Safety?
- When generalizing safety risks to other large language models that have different underlying architectures or safeguard mechanisms than GPT-3.5 Turbo. If intending to use this tool as a method of fine-tuning any model for enhancing its performance on specific tasks, given it is designed for illustrating risk rather than improving capabilities.
- Is multilingual-safety-for-LLMs or LLMs-Finetuning-Safety more popular on GitHub?
- LLMs-Finetuning-Safety has more GitHub stars (358 vs 107). Stars measure visibility, not whether either tool fits your constraints.
- Are multilingual-safety-for-LLMs and LLMs-Finetuning-Safety open source?
- Yes - both are open-source projects on GitHub (multilingual-safety-for-LLMs: MIT, LLMs-Finetuning-Safety: MIT).
- Where can I find alternatives to multilingual-safety-for-LLMs or LLMs-Finetuning-Safety?
- GraphCanon lists graph-backed alternatives at multilingual-safety-for-LLMs alternatives and LLMs-Finetuning-Safety alternatives (multilingual-safety-for-LLMs markdown twin, LLMs-Finetuning-Safety markdown twin), 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 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 LLMs-Finetuning-Safety?
- multilingual-safety-for-LLMs: Dormant. 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 multilingual-safety-for-LLMs and LLMs-Finetuning-Safety?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: multilingual-safety-for-LLMs trust report; LLMs-Finetuning-Safety trust report.