Comparison
FineTuningLLMs vs Large-Language-Model-Notebooks-Course
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.
Markdown twin · FineTuningLLMs alternatives · Large-Language-Model-Notebooks-Course alternatives
GraphCanon updated Sep 20, 2026
6views this month
vs
Large-Language-Model-Notebooks-Course
peremartra/Large-Language-Model-Notebooks-Course
★ 1.8kpushed May 28, 2026
Trust & integrity
| Signal | FineTuningLLMs | Large-Language-Model-Notebooks-Course |
|---|---|---|
| Maintenance | Slowing (203d since push) As of Sep 19, 2026 · github_public_v1 | Slowing (114d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 19, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- 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
Stars
- FineTuningLLMs
- 865
- Large-Language-Model-Notebooks-Course
- 1.8k
Forks
- FineTuningLLMs
- 119
- Large-Language-Model-Notebooks-Course
- 450
Open issues
- FineTuningLLMs
- 4
- Large-Language-Model-Notebooks-Course
- 0
Language
- FineTuningLLMs
- Jupyter Notebook
- Large-Language-Model-Notebooks-Course
- Jupyter Notebook
Adopt for
- FineTuningLLMs
- FineTuningLLMs is designed for users familiar with PyTorch and Hugging Face who seek practical guidance via Jupyter Notebooks.
- Large-Language-Model-Notebooks-Course
- A developing, comprehensive hands-on course covering a broad array of LLM tools and applications from OpenAI and Hugging Face.
Persona
- FineTuningLLMs
- -
- Large-Language-Model-Notebooks-Course
- -
Runtime
- FineTuningLLMs
- -
- Large-Language-Model-Notebooks-Course
- -
License
- FineTuningLLMs
- MIT
- Large-Language-Model-Notebooks-Course
- MIT
Last pushed
- FineTuningLLMs
- Feb 28, 2026
- Large-Language-Model-Notebooks-Course
- May 28, 2026
Categories
- FineTuningLLMs
- LLM Frameworks, Model Training
- Large-Language-Model-Notebooks-Course
- Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training
Trust and health
Days since push
- FineTuningLLMs
- 203d
- Large-Language-Model-Notebooks-Course
- 114d
Open issues (now)
- FineTuningLLMs
- 4
- Large-Language-Model-Notebooks-Course
- 0
Stars delta
- FineTuningLLMs
- +14 (30d)
- Large-Language-Model-Notebooks-Course
- +3 (30d)
Full report
- FineTuningLLMs
- Trust report
- Large-Language-Model-Notebooks-Course
- Trust report
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
When NOT to use FineTuningLLMs
- Not interested in PyTorch; prefer TensorFlow or another framework
- Seek theoretical background over practical applications
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 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (dvgodoy/FineTuningLLMs) · observed Sep 20, 2026
- GitHub forks (dvgodoy/FineTuningLLMs) · observed Sep 20, 2026
- Last push (dvgodoy/FineTuningLLMs) · observed Feb 28, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (peremartra/Large-Language-Model-Notebooks-Course) · observed Sep 20, 2026
- GitHub forks (peremartra/Large-Language-Model-Notebooks-Course) · observed Sep 20, 2026
- Last push (peremartra/Large-Language-Model-Notebooks-Course) · observed May 28, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: FineTuningLLMs 865 · Large-Language-Model-Notebooks-Course 1.8k (synced Sep 20, 2026).
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 and Large-Language-Model-Notebooks-Course alternatives (FineTuningLLMs markdown twin, Large-Language-Model-Notebooks-Course markdown twin), 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 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; Large-Language-Model-Notebooks-Course trust report.