--- title: "Hands-On-Large-Language-Models vs Visual-Adversarial-Examples-Jailbreak-Large-Language-Models" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/handsonllm-hands-on-large-language-models-vs-unispac-visual-adversarial-examples-jailbreak-large-language-models" tools: ["handsonllm-hands-on-large-language-models", "unispac-visual-adversarial-examples-jailbreak-large-language-models"] --- # Hands-On-Large-Language-Models vs Visual-Adversarial-Examples-Jailbreak-Large-Language-Models *GraphCanon updated Aug 16, 2026* ## Verdict Pick Hands-On-Large-Language-Models if consider using the 'Hands-On-Large-Language-Models' repository if your interest aligns with hands-on learning and practice of large language models through coding examples; pick Visual-Adversarial-Examples-Jailbreak-Large-Language-Models if this tool focuses on generating and studying visual adversarial examples designed to exploit vulnerabilities in large language models such as MiniGPT-4. [Hands-On-Large-Language-Models](https://www.llm-book.com/) reports 28k GitHub stars, 6.5k forks, and 38 open issues, last pushed Apr 24, 2026. [Visual-Adversarial-Examples-Jailbreak-Large-Language-Models](https://github.com/Unispac/Visual-Adversarial-Examples-Jailbreak-Large-Language-Models) has 282 stars, 30 forks, and 24 open issues, last pushed May 13, 2024. Figures are from public GitHub metadata via [Hands-On-Large-Language-Models's repository](https://github.com/HandsOnLLM/Hands-On-Large-Language-Models) and [Visual-Adversarial-Examples-Jailbreak-Large-Language-Models's repository](https://github.com/Unispac/Visual-Adversarial-Examples-Jailbreak-Large-Language-Models). | | [Hands-On-Large-Language-Models](/tools/handsonllm-hands-on-large-language-models.md) | [Visual-Adversarial-Examples-Jailbreak-Large-Language-Models](/tools/unispac-visual-adversarial-examples-jailbreak-large-language-models.md) | | --- | --- | --- | | Tagline | Official code repo for the O'Reilly Book - 'Hands-On Large Language Models' | Repository for visual adversarial examples that jailbreak large language models | | Stars | 28,252 | 282 | | Forks | 6,531 | 30 | | Open issues | 38 | 24 | | Language | Jupyter Notebook | Python | | Adopt for | Consider using the 'Hands-On-Large-Language-Models' repository if your interest aligns with hands-on learning and practice of large language models through coding examples. | This tool focuses on generating and studying visual adversarial examples designed to exploit vulnerabilities in large language models such as MiniGPT-4. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 License | - | | Categories | LLM Frameworks, Model Training | Computer Vision, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Hands-On-Large-Language-Models](/tools/handsonllm-hands-on-large-language-models.md) | [Visual-Adversarial-Examples-Jailbreak-Large-Language-Models](/tools/unispac-visual-adversarial-examples-jailbreak-large-language-models.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Dormant (18%) | | Days since push | 114d | 813d | | Open issues (now) | 38 | 24 | | Stars delta | +642 (30d) | Unknown | | Open issues delta | 0 (30d) | Unknown | | Owner type | Organization | User | | Full report | [trust report](/tools/handsonllm-hands-on-large-language-models/trust.md) | [trust report](/tools/unispac-visual-adversarial-examples-jailbreak-large-language-models/trust.md) | ## Decision facts: Hands-On-Large-Language-Models - **Pricing:** freemium - The repository is free and open under the Apache-2.0 license. - **Requirements:** - Access to Jupyter Notebook is required for running code examples provided in this repository.; - Fundamental understanding of large language models and familiarity with AI concepts would be beneficial. - **Adopt for:** Consider using the 'Hands-On-Large-Language-Models' repository if your interest aligns with hands-on learning and practice of large language models through coding examples. - **License detail:** Apache-2.0 License ## Decision facts: Visual-Adversarial-Examples-Jailbreak-Large-Language-Models - **Adopt for:** This tool focuses on generating and studying visual adversarial examples designed to exploit vulnerabilities in large language models such as MiniGPT-4. ## Choose when ### Choose Hands-On-Large-Language-Models if… - Hands-On-Large-Language-Models is primarily Jupyter Notebook; Visual-Adversarial-Examples-Jailbreak-Large-Language-Models is Python. - Pricing: The repository is free and open under the Apache-2.0 license.. - Requirements: - Access to Jupyter Notebook is required for running code examples provided in this repository.; - Fundamental understanding of large language models and familiarity with AI concepts would be beneficial.. - Tags unique to Hands-On-Large-Language-Models: artificial-intelligence, book, large language models, llm. - Also covers LLM Frameworks. - - You are focusing on practical implementation aspects detailed in a structured format as outlined by O'Reilly's authoritative book. ### Choose Visual-Adversarial-Examples-Jailbreak-Large-Language-Models if… - Visual-Adversarial-Examples-Jailbreak-Large-Language-Models is primarily Python; Hands-On-Large-Language-Models is Jupyter Notebook. - Tags unique to Visual-Adversarial-Examples-Jailbreak-Large-Language-Models: large-language-model, visual adversarial. - Also covers Computer Vision. - If your goal is to research the resilience of Large Language Models against visual inputs that could mislead or 'jailbreak' their usual behavior. ## When NOT to use Hands-On-Large-Language-Models - - If you need real-time model evaluation tools rather than educational materials, as this repository primarily provides code for understanding and implementing concepts covered in a book. - - You are seeking proprietary or more specialized frameworks that go beyond the examples provided in an educational context to meet specific, advanced use-case needs. ## When NOT to use Visual-Adversarial-Examples-Jailbreak-Large-Language-Models - Avoid using this tool if your objective does not involve security testing or research concerning visual-linguistic interactions with large language models. - If you are looking to enhance general-purpose AI applications without considering adversarial attacks, other frameworks would be more appropriate. ## Common questions ### What is the difference between Hands-On-Large-Language-Models and Visual-Adversarial-Examples-Jailbreak-Large-Language-Models? Hands-On-Large-Language-Models: Official code repo for the O'Reilly Book - 'Hands-On Large Language Models'. Visual-Adversarial-Examples-Jailbreak-Large-Language-Models: Repository for visual adversarial examples that jailbreak large language models. See the comparison table for live GitHub stats and shared categories. ### When should I choose Hands-On-Large-Language-Models over Visual-Adversarial-Examples-Jailbreak-Large-Language-Models? Choose Hands-On-Large-Language-Models over Visual-Adversarial-Examples-Jailbreak-Large-Language-Models when Hands-On-Large-Language-Models is primarily Jupyter Notebook; Visual-Adversarial-Examples-Jailbreak-Large-Language-Models is Python; Pricing: The repository is free and open under the Apache-2.0 license.; Requirements: - Access to Jupyter Notebook is required for running code examples provided in this repository.; - Fundamental understanding of large language models and familiarity with AI concepts would be beneficial.; Tags unique to Hands-On-Large-Language-Models: artificial-intelligence, book, large language models, llm; Also covers LLM Frameworks; - You are focusing on practical implementation aspects detailed in a structured format as outlined by O'Reilly's authoritative book. ### When should I choose Visual-Adversarial-Examples-Jailbreak-Large-Language-Models over Hands-On-Large-Language-Models? Choose Visual-Adversarial-Examples-Jailbreak-Large-Language-Models over Hands-On-Large-Language-Models when Visual-Adversarial-Examples-Jailbreak-Large-Language-Models is primarily Python; Hands-On-Large-Language-Models is Jupyter Notebook; Tags unique to Visual-Adversarial-Examples-Jailbreak-Large-Language-Models: large-language-model, visual adversarial; Also covers Computer Vision; If your goal is to research the resilience of Large Language Models against visual inputs that could mislead or 'jailbreak' their usual behavior. ### When should I avoid Hands-On-Large-Language-Models? - If you need real-time model evaluation tools rather than educational materials, as this repository primarily provides code for understanding and implementing concepts covered in a book. - You are seeking proprietary or more specialized frameworks that go beyond the examples provided in an educational context to meet specific, advanced use-case needs. ### When should I avoid Visual-Adversarial-Examples-Jailbreak-Large-Language-Models? Avoid using this tool if your objective does not involve security testing or research concerning visual-linguistic interactions with large language models. If you are looking to enhance general-purpose AI applications without considering adversarial attacks, other frameworks would be more appropriate. ### Is Hands-On-Large-Language-Models or Visual-Adversarial-Examples-Jailbreak-Large-Language-Models more popular on GitHub? Hands-On-Large-Language-Models has more GitHub stars (28,252 vs 282). Stars measure visibility, not whether either tool fits your constraints. ### Are Hands-On-Large-Language-Models and Visual-Adversarial-Examples-Jailbreak-Large-Language-Models open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to Hands-On-Large-Language-Models or Visual-Adversarial-Examples-Jailbreak-Large-Language-Models? GraphCanon lists graph-backed alternatives at [Hands-On-Large-Language-Models alternatives](/tools/handsonllm-hands-on-large-language-models/alternatives) and [Visual-Adversarial-Examples-Jailbreak-Large-Language-Models alternatives](/tools/unispac-visual-adversarial-examples-jailbreak-large-language-models/alternatives) ([Hands-On-Large-Language-Models markdown twin](/tools/handsonllm-hands-on-large-language-models/alternatives.md), [Visual-Adversarial-Examples-Jailbreak-Large-Language-Models markdown twin](/tools/unispac-visual-adversarial-examples-jailbreak-large-language-models/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/handsonllm-hands-on-large-language-models-vs-unispac-visual-adversarial-examples-jailbreak-large-language-models.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Hands-On-Large-Language-Models or Visual-Adversarial-Examples-Jailbreak-Large-Language-Models? Hands-On-Large-Language-Models: Slowing. Visual-Adversarial-Examples-Jailbreak-Large-Language-Models: 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 Hands-On-Large-Language-Models and Visual-Adversarial-Examples-Jailbreak-Large-Language-Models? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Hands-On-Large-Language-Models trust report](/tools/handsonllm-hands-on-large-language-models/trust); [Visual-Adversarial-Examples-Jailbreak-Large-Language-Models trust report](/tools/unispac-visual-adversarial-examples-jailbreak-large-language-models/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=handsonllm-hands-on-large-language-models`](/api/graphcanon/graph?tool=handsonllm-hands-on-large-language-models) - 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/_