--- title: "Hands-On-Large-Language-Models vs pallms" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/handsonllm-hands-on-large-language-models-vs-mik0w-pallms" tools: ["handsonllm-hands-on-large-language-models", "mik0w-pallms"] --- # Hands-On-Large-Language-Models vs pallms *GraphCanon updated Oct 6, 2026* ## Verdict Pick Hands-On-Large-Language-Models if hands-On-Large-Language-Models offers code examples and educational content for large language models, as detailed in the O'Reilly book 'Hands-On Large Language Models'. The repository is in Jupyter Notebook format and,遵; pick pallms if pallms is a collection of payloads designed to test vulnerabilities in large language models through prompt injection attacks. [Hands-On-Large-Language-Models](https://www.llm-book.com/) reports 29k GitHub stars, 6.7k forks, and 40 open issues, last pushed Apr 24, 2026. [pallms](https://github.com/mik0w/pallms) has 149 stars, 19 forks, and 0 open issues, last pushed Jan 13, 2026. Figures are from public GitHub metadata via [Hands-On-Large-Language-Models's repository](https://github.com/HandsOnLLM/Hands-On-Large-Language-Models) and [pallms's repository](https://github.com/mik0w/pallms). | | [Hands-On-Large-Language-Models](/tools/handsonllm-hands-on-large-language-models.md) | [pallms](/tools/mik0w-pallms.md) | | --- | --- | --- | | Tagline | Code for the book 'Hands-On Large Language Models' | Payloads for attacking Large Language Models | | Stars | 29,162 | 149 | | Forks | 6,662 | 19 | | Open issues | 40 | 0 | | Language | Jupyter Notebook | - | | Adopt for | Hands-On-Large-Language-Models offers code examples and educational content for large language models, as detailed in the O'Reilly book 'Hands-On Large Language Models'. The repository is in Jupyter Notebook format and,遵 | Pallms is a collection of payloads designed to test vulnerabilities in large language models through prompt injection attacks. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Developer Tools, LLM Frameworks | LLM Frameworks | ## 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) | [pallms](/tools/mik0w-pallms.md) | | --- | --- | --- | | Days since push | 146d | 265d | | Open issues (now) | 40 | 0 | | Stars delta | +910 (30d) | +4 (30d) | | Open issues delta | +2 (30d) | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/handsonllm-hands-on-large-language-models/trust.md) | [trust report](/tools/mik0w-pallms/trust.md) | ## Decision facts: Hands-On-Large-Language-Models - **Adopt for:** Hands-On-Large-Language-Models offers code examples and educational content for large language models, as detailed in the O'Reilly book 'Hands-On Large Language Models'. The repository is in Jupyter Notebook format and,遵 ## Decision facts: pallms - **Adopt for:** Pallms is a collection of payloads designed to test vulnerabilities in large language models through prompt injection attacks. ## Choose when ### Choose Hands-On-Large-Language-Models if… - License: Hands-On-Large-Language-Models is Apache-2.0, pallms is MIT. - Tags unique to Hands-On-Large-Language-Models: artificial-intelligence, book, large-language-models, llm. - Also covers Developer Tools. - Use this tool if you are looking for practical, code-based learning resources that align with the book 'Hands-On Large Language Models'. ### Choose pallms if… - License: pallms is MIT, Hands-On-Large-Language-Models is Apache-2.0. - Tags unique to pallms: prompt-injection, security-testing, vulnerability-assessment. - When you need specific payloads for testing and validating the security of your LLM against prompt injection attacks. ## When NOT to use Hands-On-Large-Language-Models - Avoid this tool if you are seeking a comprehensive theoretical background without practical examples, as the focus is on hands-on learning. - Not recommended for users who prefer a different platform for running code examples, as the repository is optimized for Google Colab with a T4 GPU and 16GB VRAM. - If you are looking for a tool that covers a broader range of AI topics beyond large language models, this repository may not be the best fit. ## When NOT to use pallms - If you require a framework for general development or deployment of large language model applications outside the scope of security testing. - When looking for tools that offer comprehensive protection against all types of LLM vulnerabilities, as Pallms focuses primarily on prompt injection. ## Common questions ### What is the difference between Hands-On-Large-Language-Models and pallms? Hands-On-Large-Language-Models: Code for the book 'Hands-On Large Language Models'. pallms: Payloads for attacking Large Language Models. See the comparison table for live GitHub stats and shared categories. ### When should I choose Hands-On-Large-Language-Models over pallms? Choose Hands-On-Large-Language-Models over pallms when License: Hands-On-Large-Language-Models is Apache-2.0, pallms is MIT; Tags unique to Hands-On-Large-Language-Models: artificial-intelligence, book, large-language-models, llm; Also covers Developer Tools; Use this tool if you are looking for practical, code-based learning resources that align with the book 'Hands-On Large Language Models'. ### When should I choose pallms over Hands-On-Large-Language-Models? Choose pallms over Hands-On-Large-Language-Models when License: pallms is MIT, Hands-On-Large-Language-Models is Apache-2.0; Tags unique to pallms: prompt-injection, security-testing, vulnerability-assessment; When you need specific payloads for testing and validating the security of your LLM against prompt injection attacks. ### When should I avoid Hands-On-Large-Language-Models? Avoid this tool if you are seeking a comprehensive theoretical background without practical examples, as the focus is on hands-on learning. Not recommended for users who prefer a different platform for running code examples, as the repository is optimized for Google Colab with a T4 GPU and 16GB VRAM. If you are looking for a tool that covers a broader range of AI topics beyond large language models, this repository may not be the best fit. ### When should I avoid pallms? If you require a framework for general development or deployment of large language model applications outside the scope of security testing. When looking for tools that offer comprehensive protection against all types of LLM vulnerabilities, as Pallms focuses primarily on prompt injection. ### Is Hands-On-Large-Language-Models or pallms more popular on GitHub? Hands-On-Large-Language-Models has more GitHub stars (29,162 vs 149). Stars measure visibility, not whether either tool fits your constraints. ### Are Hands-On-Large-Language-Models and pallms open source? Yes - both are open-source projects on GitHub (Hands-On-Large-Language-Models: Apache-2.0, pallms: MIT). ### Where can I find alternatives to Hands-On-Large-Language-Models or pallms? GraphCanon lists graph-backed alternatives at [Hands-On-Large-Language-Models alternatives](/tools/handsonllm-hands-on-large-language-models/alternatives) and [pallms alternatives](/tools/mik0w-pallms/alternatives) ([Hands-On-Large-Language-Models markdown twin](/tools/handsonllm-hands-on-large-language-models/alternatives.md), [pallms markdown twin](/tools/mik0w-pallms/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-mik0w-pallms.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 pallms? Hands-On-Large-Language-Models: Slowing. pallms: Slowing. 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 pallms? 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); [pallms trust report](/tools/mik0w-pallms/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/_