--- title: "awesome-llms-fine-tuning vs ell" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/curated-awesome-lists-awesome-llms-fine-tuning-vs-madcowd-ell" tools: ["curated-awesome-lists-awesome-llms-fine-tuning", "madcowd-ell"] --- # awesome-llms-fine-tuning vs ell *GraphCanon updated Aug 24, 2026* ## Verdict Pick awesome-llms-fine-tuning if a curated list for LLM fine-tuning resources including tutorials, papers, and tools; pick ell if ell is a Python-based language model development library and prompt engineering tool. [awesome-llms-fine-tuning](https://github.com/Curated-Awesome-Lists/awesome-llms-fine-tuning) reports 525 GitHub stars, 79 forks, and 10 open issues, last pushed Dec 2, 2024. [ell](http://docs.ell.so/) has 5.9k stars, 343 forks, and 186 open issues, last pushed Jun 5, 2025. Figures are from public GitHub metadata via [awesome-llms-fine-tuning's repository](https://github.com/Curated-Awesome-Lists/awesome-llms-fine-tuning) and [ell's repository](https://github.com/MadcowD/ell). | | [awesome-llms-fine-tuning](/tools/curated-awesome-lists-awesome-llms-fine-tuning.md) | [ell](/tools/madcowd-ell.md) | | --- | --- | --- | | Tagline | A comprehensive collection of resources for fine-tuning Large Language Models. | A language model programming library | | Stars | 525 | 5,869 | | Forks | 79 | 343 | | Open issues | 10 | 186 | | Language | - | Python | | Adopt for | A curated list for LLM fine-tuning resources including tutorials, papers, and tools. | ell is a Python-based language model development library and prompt engineering tool. | | Persona | - | - | | Runtime | - | - | | License | (unknown) - (unknown) | MIT - Permissive free software license | | Categories | LLM Frameworks, Model Training | LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-llms-fine-tuning](/tools/curated-awesome-lists-awesome-llms-fine-tuning.md) | [ell](/tools/madcowd-ell.md) | | --- | --- | --- | | Days since push | 629d | 417d | | Open issues (now) | 10 | 186 | | Stars delta | 0 (30d) | Unknown | | Open issues delta | +1 (30d) | Unknown | | Owner type | Organization | User | | Full report | [trust report](/tools/curated-awesome-lists-awesome-llms-fine-tuning/trust.md) | [trust report](/tools/madcowd-ell/trust.md) | ## Decision facts: awesome-llms-fine-tuning - **Adopt for:** A curated list for LLM fine-tuning resources including tutorials, papers, and tools. - **License detail:** (unknown) - (unknown) ## Decision facts: ell - **Pricing:** freemium - Free to use under MIT License, with no premium plans mentioned. - **Adopt for:** ell is a Python-based language model development library and prompt engineering tool. - **License detail:** MIT - Permissive free software license ## Choose when ### Choose awesome-llms-fine-tuning if… - Tags unique to awesome-llms-fine-tuning: awesome-list, deep-learning, fine-tuning, gpt. - Also covers Model Training. - Need extensive guidance on LLM-specific fine-tuning strategies ### Choose ell if… - Pricing: Free to use under MIT License, with no premium plans mentioned.. - Tags unique to ell: prompt-engineering. - When you require a dedicated Python framework for developing custom language models and fine-tuning them with specific prompts for your application. ## When NOT to use awesome-llms-fine-tuning - Looking for real-time interactive support or direct code implementation help - Favor more specialized tools for immediate performance optimization over broad learning ## When NOT to use ell - If you prefer JavaScript or other languages over Python, consider alternative frameworks that support the language of your choice. ## Common questions ### What is the difference between awesome-llms-fine-tuning and ell? awesome-llms-fine-tuning: A comprehensive collection of resources for fine-tuning Large Language Models.. ell: A language model programming library. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-llms-fine-tuning over ell? Choose awesome-llms-fine-tuning over ell when Tags unique to awesome-llms-fine-tuning: awesome-list, deep-learning, fine-tuning, gpt; Also covers Model Training; Need extensive guidance on LLM-specific fine-tuning strategies. ### When should I choose ell over awesome-llms-fine-tuning? Choose ell over awesome-llms-fine-tuning when Pricing: Free to use under MIT License, with no premium plans mentioned.; Tags unique to ell: prompt-engineering; When you require a dedicated Python framework for developing custom language models and fine-tuning them with specific prompts for your application. ### When should I avoid awesome-llms-fine-tuning? Looking for real-time interactive support or direct code implementation help Favor more specialized tools for immediate performance optimization over broad learning ### When should I avoid ell? If you prefer JavaScript or other languages over Python, consider alternative frameworks that support the language of your choice. ### Is awesome-llms-fine-tuning or ell more popular on GitHub? ell has more GitHub stars (5,869 vs 525). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-llms-fine-tuning and ell open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to awesome-llms-fine-tuning or ell? GraphCanon lists graph-backed alternatives at [awesome-llms-fine-tuning alternatives](/tools/curated-awesome-lists-awesome-llms-fine-tuning/alternatives) and [ell alternatives](/tools/madcowd-ell/alternatives) ([awesome-llms-fine-tuning markdown twin](/tools/curated-awesome-lists-awesome-llms-fine-tuning/alternatives.md), [ell markdown twin](/tools/madcowd-ell/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/curated-awesome-lists-awesome-llms-fine-tuning-vs-madcowd-ell.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome-llms-fine-tuning or ell? awesome-llms-fine-tuning: Dormant. ell: 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 awesome-llms-fine-tuning and ell? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-llms-fine-tuning trust report](/tools/curated-awesome-lists-awesome-llms-fine-tuning/trust); [ell trust report](/tools/madcowd-ell/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=curated-awesome-lists-awesome-llms-fine-tuning`](/api/graphcanon/graph?tool=curated-awesome-lists-awesome-llms-fine-tuning) - 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/_