--- title: "FineTuningLLMs vs SPIN" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dvgodoy-finetuningllms-vs-uclaml-spin" tools: ["dvgodoy-finetuningllms", "uclaml-spin"] --- # FineTuningLLMs vs SPIN *GraphCanon updated Aug 24, 2026* ## Verdict Pick FineTuningLLMs if fineTuningLLMs is designed for users familiar with PyTorch and Hugging Face who seek practical guidance via Jupyter Notebooks; pick SPIN if sPIN is specialized for self-play fine-tuning in large language models through deep learning. [FineTuningLLMs](https://github.com/dvgodoy/FineTuningLLMs) reports 855 GitHub stars, 116 forks, and 4 open issues, last pushed Feb 28, 2026. [SPIN](https://uclaml.github.io/SPIN/) has 1.3k stars, 106 forks, and 24 open issues, last pushed May 8, 2024. Figures are from public GitHub metadata via [FineTuningLLMs's repository](https://github.com/dvgodoy/FineTuningLLMs) and [SPIN's repository](https://github.com/uclaml/SPIN). | | [FineTuningLLMs](/tools/dvgodoy-finetuningllms.md) | [SPIN](/tools/uclaml-spin.md) | | --- | --- | --- | | Tagline | Official repository for 'A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face' | Official implementation of Self-Play Fine-Tuning | | Stars | 855 | 1,254 | | Forks | 116 | 106 | | Open issues | 4 | 24 | | Language | Jupyter Notebook | Python | | Adopt for | FineTuningLLMs is designed for users familiar with PyTorch and Hugging Face who seek practical guidance via Jupyter Notebooks. | SPIN is specialized for self-play fine-tuning in large language models through deep learning. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [FineTuningLLMs](/tools/dvgodoy-finetuningllms.md) | [SPIN](/tools/uclaml-spin.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Dormant (18%) | | Days since push | 176d | 837d | | Open issues (now) | 4 | 24 | | Stars delta | +4 (30d) | +6 (30d) | | Full report | [trust report](/tools/dvgodoy-finetuningllms/trust.md) | [trust report](/tools/uclaml-spin/trust.md) | ## Decision facts: FineTuningLLMs - **Adopt for:** FineTuningLLMs is designed for users familiar with PyTorch and Hugging Face who seek practical guidance via Jupyter Notebooks. ## Decision facts: SPIN - **Adopt for:** SPIN is specialized for self-play fine-tuning in large language models through deep learning. ## Choose when ### Choose FineTuningLLMs if… - FineTuningLLMs is primarily Jupyter Notebook; SPIN is Python. - License: FineTuningLLMs is MIT, SPIN is Apache-2.0. - Tags unique to FineTuningLLMs: bitsandbytes, finetuning, hugging-face, llamacpp. - You need hands-on, step-by-step instructions using PyTorch and the Hugging Face ecosystem ### Choose SPIN if… - SPIN is primarily Python; FineTuningLLMs is Jupyter Notebook. - License: SPIN is Apache-2.0, FineTuningLLMs is MIT. - Tags unique to SPIN: deep-learning, self-play. - When implementing self-play algorithms aimed at enhancing performance of large language models within constrained domains. ## When NOT to use FineTuningLLMs - Not interested in PyTorch; prefer TensorFlow or another framework - Seek theoretical background over practical applications ## When NOT to use SPIN - If your project strictly adheres to frameworks that do not incorporate self-play techniques for training or fine-tuning models. - When prioritizing a model training framework that relies on supervised learning rather than the self-play methodology SPIN is based upon. ## Common questions ### What is the difference between FineTuningLLMs and SPIN? FineTuningLLMs: Official repository for 'A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face'. SPIN: Official implementation of Self-Play Fine-Tuning. See the comparison table for live GitHub stats and shared categories. ### When should I choose FineTuningLLMs over SPIN? Choose FineTuningLLMs over SPIN when FineTuningLLMs is primarily Jupyter Notebook; SPIN is Python; License: FineTuningLLMs is MIT, SPIN is Apache-2.0; Tags unique to FineTuningLLMs: bitsandbytes, finetuning, hugging-face, llamacpp; You need hands-on, step-by-step instructions using PyTorch and the Hugging Face ecosystem. ### When should I choose SPIN over FineTuningLLMs? Choose SPIN over FineTuningLLMs when SPIN is primarily Python; FineTuningLLMs is Jupyter Notebook; License: SPIN is Apache-2.0, FineTuningLLMs is MIT; Tags unique to SPIN: deep-learning, self-play; When implementing self-play algorithms aimed at enhancing performance of large language models within constrained domains. ### When should I avoid FineTuningLLMs? Not interested in PyTorch; prefer TensorFlow or another framework Seek theoretical background over practical applications ### When should I avoid SPIN? If your project strictly adheres to frameworks that do not incorporate self-play techniques for training or fine-tuning models. When prioritizing a model training framework that relies on supervised learning rather than the self-play methodology SPIN is based upon. ### Is FineTuningLLMs or SPIN more popular on GitHub? SPIN has more GitHub stars (1,254 vs 855). Stars measure visibility, not whether either tool fits your constraints. ### Are FineTuningLLMs and SPIN open source? Yes - both are open-source projects on GitHub (FineTuningLLMs: MIT, SPIN: Apache-2.0). ### Where can I find alternatives to FineTuningLLMs or SPIN? GraphCanon lists graph-backed alternatives at [FineTuningLLMs alternatives](/tools/dvgodoy-finetuningllms/alternatives) and [SPIN alternatives](/tools/uclaml-spin/alternatives) ([FineTuningLLMs markdown twin](/tools/dvgodoy-finetuningllms/alternatives.md), [SPIN markdown twin](/tools/uclaml-spin/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/dvgodoy-finetuningllms-vs-uclaml-spin.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, FineTuningLLMs or SPIN? FineTuningLLMs: Slowing. SPIN: 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 FineTuningLLMs and SPIN? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FineTuningLLMs trust report](/tools/dvgodoy-finetuningllms/trust); [SPIN trust report](/tools/uclaml-spin/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=dvgodoy-finetuningllms`](/api/graphcanon/graph?tool=dvgodoy-finetuningllms) - 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/_