--- title: "FineTuningLLMs vs Large-Language-Model-Notebooks-Course" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dvgodoy-finetuningllms-vs-peremartra-large-language-model-notebooks-course" tools: ["dvgodoy-finetuningllms", "peremartra-large-language-model-notebooks-course"] --- # FineTuningLLMs vs Large-Language-Model-Notebooks-Course *GraphCanon updated Sep 20, 2026* ## Verdict Pick FineTuningLLMs if fineTuningLLMs is designed for users familiar with PyTorch and Hugging Face who seek practical guidance via Jupyter Notebooks; pick Large-Language-Model-Notebooks-Course if a developing, comprehensive hands-on course covering a broad array of LLM tools and applications from OpenAI and Hugging Face. [FineTuningLLMs](https://github.com/dvgodoy/FineTuningLLMs) reports 865 GitHub stars, 119 forks, and 4 open issues, last pushed Feb 28, 2026. [Large-Language-Model-Notebooks-Course](https://medium.com/@peremartra/list/large-language-models-practical-course-66b4ce5943ce) has 1.8k stars, 450 forks, and 0 open issues, last pushed May 28, 2026. Figures are from public GitHub metadata via [FineTuningLLMs's repository](https://github.com/dvgodoy/FineTuningLLMs) and [Large-Language-Model-Notebooks-Course's repository](https://github.com/peremartra/Large-Language-Model-Notebooks-Course). | | [FineTuningLLMs](/tools/dvgodoy-finetuningllms.md) | [Large-Language-Model-Notebooks-Course](/tools/peremartra-large-language-model-notebooks-course.md) | | --- | --- | --- | | Tagline | Official repository for 'A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face' | Practical course about Large Language Models | | Stars | 865 | 1,824 | | Forks | 119 | 450 | | Open issues | 4 | 0 | | 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. | A developing, comprehensive hands-on course covering a broad array of LLM tools and applications from OpenAI and Hugging Face. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | LLM Frameworks, Model Training | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [FineTuningLLMs](/tools/dvgodoy-finetuningllms.md) | [Large-Language-Model-Notebooks-Course](/tools/peremartra-large-language-model-notebooks-course.md) | | --- | --- | --- | | Days since push | 203d | 114d | | Open issues (now) | 4 | 0 | | Stars delta | +14 (30d) | +3 (30d) | | Full report | [trust report](/tools/dvgodoy-finetuningllms/trust.md) | [trust report](/tools/peremartra-large-language-model-notebooks-course/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: Large-Language-Model-Notebooks-Course - **Adopt for:** A developing, comprehensive hands-on course covering a broad array of LLM tools and applications from OpenAI and Hugging Face. ## Choose when ### Choose FineTuningLLMs if… - Tags unique to FineTuningLLMs: bitsandbytes, fine-tuning, finetuning, hugging-face. - You need hands-on, step-by-step instructions using PyTorch and the Hugging Face ecosystem ### Choose Large-Language-Model-Notebooks-Course if… - Tags unique to Large-Language-Model-Notebooks-Course: chatbots, fine-tuning-llm, huggingface, langchain. - Also covers Evaluation & Observability, Inference & Serving. - You're seeking an evolving curriculum with projects that apply Large Language Model techniques from various libraries. ## When NOT to use FineTuningLLMs - Not interested in PyTorch; prefer TensorFlow or another framework - Seek theoretical background over practical applications ## When NOT to use Large-Language-Model-Notebooks-Course - Seeking a complete, finalized course where all content is available for immediate use without future updates. - Looking exclusively for theory; the course emphasizes practical application over theoretical depth. ## Common questions ### What is the difference between FineTuningLLMs and Large-Language-Model-Notebooks-Course? FineTuningLLMs: Official repository for 'A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face'. Large-Language-Model-Notebooks-Course: Practical course about Large Language Models. See the comparison table for live GitHub stats and shared categories. ### When should I choose FineTuningLLMs over Large-Language-Model-Notebooks-Course? Choose FineTuningLLMs over Large-Language-Model-Notebooks-Course when Tags unique to FineTuningLLMs: bitsandbytes, fine-tuning, finetuning, hugging-face; You need hands-on, step-by-step instructions using PyTorch and the Hugging Face ecosystem. ### When should I choose Large-Language-Model-Notebooks-Course over FineTuningLLMs? Choose Large-Language-Model-Notebooks-Course over FineTuningLLMs when Tags unique to Large-Language-Model-Notebooks-Course: chatbots, fine-tuning-llm, huggingface, langchain; Also covers Evaluation & Observability, Inference & Serving; You're seeking an evolving curriculum with projects that apply Large Language Model techniques from various libraries. ### When should I avoid FineTuningLLMs? Not interested in PyTorch; prefer TensorFlow or another framework Seek theoretical background over practical applications ### When should I avoid Large-Language-Model-Notebooks-Course? Seeking a complete, finalized course where all content is available for immediate use without future updates. Looking exclusively for theory; the course emphasizes practical application over theoretical depth. ### Is FineTuningLLMs or Large-Language-Model-Notebooks-Course more popular on GitHub? Large-Language-Model-Notebooks-Course has more GitHub stars (1,824 vs 865). Stars measure visibility, not whether either tool fits your constraints. ### Are FineTuningLLMs and Large-Language-Model-Notebooks-Course open source? Yes - both are open-source projects on GitHub (FineTuningLLMs: MIT, Large-Language-Model-Notebooks-Course: MIT). ### Where can I find alternatives to FineTuningLLMs or Large-Language-Model-Notebooks-Course? GraphCanon lists graph-backed alternatives at [FineTuningLLMs alternatives](/tools/dvgodoy-finetuningllms/alternatives) and [Large-Language-Model-Notebooks-Course alternatives](/tools/peremartra-large-language-model-notebooks-course/alternatives) ([FineTuningLLMs markdown twin](/tools/dvgodoy-finetuningllms/alternatives.md), [Large-Language-Model-Notebooks-Course markdown twin](/tools/peremartra-large-language-model-notebooks-course/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-peremartra-large-language-model-notebooks-course.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, FineTuningLLMs or Large-Language-Model-Notebooks-Course? FineTuningLLMs: Slowing. Large-Language-Model-Notebooks-Course: 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 FineTuningLLMs and Large-Language-Model-Notebooks-Course? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FineTuningLLMs trust report](/tools/dvgodoy-finetuningllms/trust); [Large-Language-Model-Notebooks-Course trust report](/tools/peremartra-large-language-model-notebooks-course/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/_