--- title: "FineTuningLLMs vs Jackrong-llm-finetuning-guide" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dvgodoy-finetuningllms-vs-r6410418-jackrong-llm-finetuning-guide" tools: ["dvgodoy-finetuningllms", "r6410418-jackrong-llm-finetuning-guide"] --- # FineTuningLLMs vs Jackrong-llm-finetuning-guide *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 Jackrong-llm-finetuning-guide if jackrong-llm-finetuning-guide: A targeted instructive resource for those seeking to fine-tune their large language models such as LLaMA3 and Qwen using PyTorch. [FineTuningLLMs](https://github.com/dvgodoy/FineTuningLLMs) reports 855 GitHub stars, 116 forks, and 4 open issues, last pushed Feb 28, 2026. [Jackrong-llm-finetuning-guide](https://r6410418.github.io/Jackrong-llm-finetuning-guide/) has 1.7k stars, 269 forks, and 11 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [FineTuningLLMs's repository](https://github.com/dvgodoy/FineTuningLLMs) and [Jackrong-llm-finetuning-guide's repository](https://github.com/R6410418/Jackrong-llm-finetuning-guide). | | [FineTuningLLMs](/tools/dvgodoy-finetuningllms.md) | [Jackrong-llm-finetuning-guide](/tools/r6410418-jackrong-llm-finetuning-guide.md) | | --- | --- | --- | | Tagline | Official repository for 'A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face' | A guide for fine-tuning large language models like LLaMA3 and Qwen using PyTorch | | Stars | 855 | 1,661 | | Forks | 116 | 269 | | Open issues | 4 | 11 | | Language | Jupyter Notebook | Jupyter Notebook | | Adopt for | FineTuningLLMs is designed for users familiar with PyTorch and Hugging Face who seek practical guidance via Jupyter Notebooks. | Jackrong-llm-finetuning-guide: A targeted instructive resource for those seeking to fine-tune their large language models such as LLaMA3 and Qwen using PyTorch. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache License Version 2.0: Permits free use, distribution and modification of the software. | | 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) | [Jackrong-llm-finetuning-guide](/tools/r6410418-jackrong-llm-finetuning-guide.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Steady (60%) | | Days since push | 176d | 43d | | Open issues (now) | 4 | 11 | | Stars delta | +4 (30d) | +57 (30d) | | Full report | [trust report](/tools/dvgodoy-finetuningllms/trust.md) | [trust report](/tools/r6410418-jackrong-llm-finetuning-guide/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: Jackrong-llm-finetuning-guide - **Requirements:** Requires Python environment setup for PyTorch and Jupyter Notebook familiarity. - **Adopt for:** Jackrong-llm-finetuning-guide: A targeted instructive resource for those seeking to fine-tune their large language models such as LLaMA3 and Qwen using PyTorch. - **License detail:** Apache License Version 2.0: Permits free use, distribution and modification of the software. ## Choose when ### Choose FineTuningLLMs if… - License: FineTuningLLMs is MIT, Jackrong-llm-finetuning-guide is Apache-2.0. - Tags unique to FineTuningLLMs: bitsandbytes, finetuning, hugging-face, large language models. - You need hands-on, step-by-step instructions using PyTorch and the Hugging Face ecosystem ### Choose Jackrong-llm-finetuning-guide if… - License: Jackrong-llm-finetuning-guide is Apache-2.0, FineTuningLLMs is MIT. - Requirements: Requires Python environment setup for PyTorch and Jupyter Notebook familiarity.. - Tags unique to Jackrong-llm-finetuning-guide: dataset, deepseek, llama3, llm. - You are specifically working with or planning to work with LLaMA3 or Qwen models, which this guide exclusively supports. ## When NOT to use FineTuningLLMs - Not interested in PyTorch; prefer TensorFlow or another framework - Seek theoretical background over practical applications ## When NOT to use Jackrong-llm-finetuning-guide - You prefer TensorFlow (or another deep learning framework not covered by Jackrong-llm-finetuning-guide) as your primary environment for developing AI models. - Your interest lies in general knowledge about LLMs without the specifics of implementation or fine-tuning methodologies. ## Common questions ### What is the difference between FineTuningLLMs and Jackrong-llm-finetuning-guide? FineTuningLLMs: Official repository for 'A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face'. Jackrong-llm-finetuning-guide: A guide for fine-tuning large language models like LLaMA3 and Qwen using PyTorch. See the comparison table for live GitHub stats and shared categories. ### When should I choose FineTuningLLMs over Jackrong-llm-finetuning-guide? Choose FineTuningLLMs over Jackrong-llm-finetuning-guide when License: FineTuningLLMs is MIT, Jackrong-llm-finetuning-guide is Apache-2.0; Tags unique to FineTuningLLMs: bitsandbytes, finetuning, hugging-face, large language models; You need hands-on, step-by-step instructions using PyTorch and the Hugging Face ecosystem. ### When should I choose Jackrong-llm-finetuning-guide over FineTuningLLMs? Choose Jackrong-llm-finetuning-guide over FineTuningLLMs when License: Jackrong-llm-finetuning-guide is Apache-2.0, FineTuningLLMs is MIT; Requirements: Requires Python environment setup for PyTorch and Jupyter Notebook familiarity.; Tags unique to Jackrong-llm-finetuning-guide: dataset, deepseek, llama3, llm; You are specifically working with or planning to work with LLaMA3 or Qwen models, which this guide exclusively supports. ### When should I avoid FineTuningLLMs? Not interested in PyTorch; prefer TensorFlow or another framework Seek theoretical background over practical applications ### When should I avoid Jackrong-llm-finetuning-guide? You prefer TensorFlow (or another deep learning framework not covered by Jackrong-llm-finetuning-guide) as your primary environment for developing AI models. Your interest lies in general knowledge about LLMs without the specifics of implementation or fine-tuning methodologies. ### Is FineTuningLLMs or Jackrong-llm-finetuning-guide more popular on GitHub? Jackrong-llm-finetuning-guide has more GitHub stars (1,661 vs 855). Stars measure visibility, not whether either tool fits your constraints. ### Are FineTuningLLMs and Jackrong-llm-finetuning-guide open source? Yes - both are open-source projects on GitHub (FineTuningLLMs: MIT, Jackrong-llm-finetuning-guide: Apache-2.0). ### Where can I find alternatives to FineTuningLLMs or Jackrong-llm-finetuning-guide? GraphCanon lists graph-backed alternatives at [FineTuningLLMs alternatives](/tools/dvgodoy-finetuningllms/alternatives) and [Jackrong-llm-finetuning-guide alternatives](/tools/r6410418-jackrong-llm-finetuning-guide/alternatives) ([FineTuningLLMs markdown twin](/tools/dvgodoy-finetuningllms/alternatives.md), [Jackrong-llm-finetuning-guide markdown twin](/tools/r6410418-jackrong-llm-finetuning-guide/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-r6410418-jackrong-llm-finetuning-guide.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, FineTuningLLMs or Jackrong-llm-finetuning-guide? FineTuningLLMs: Slowing. Jackrong-llm-finetuning-guide: Steady. 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 Jackrong-llm-finetuning-guide? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FineTuningLLMs trust report](/tools/dvgodoy-finetuningllms/trust); [Jackrong-llm-finetuning-guide trust report](/tools/r6410418-jackrong-llm-finetuning-guide/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/_