Comparison
FineTuningLLMs vs LlamaFactory
Verdict
Pick FineTuningLLMs when fineTuningLLMs is primarily Jupyter Notebook; LlamaFactory is Python; pick LlamaFactory when llamaFactory is primarily Python; FineTuningLLMs is Jupyter Notebook.
Markdown twin · FineTuningLLMs alternatives · LlamaFactory alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | FineTuningLLMs | LlamaFactory |
|---|---|---|
| Maintenance | Slowing (132d since push) As of today · github_public_v1 | Very active (0d since push) As of 1d · github_public_v1 |
| Provenance | Not a fork · Personal account As of today · github_public_v1 | Not a fork · Personal account As of 1d · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No lockfile As of 1d · none |
Tagline
- FineTuningLLMs
- Official repository of my book "A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face"
- LlamaFactory
- Unified Efficient Fine-Tuning of 100+ LLMs & VLMs
Stars
- FineTuningLLMs
- 848
- LlamaFactory
- 73k
Forks
- FineTuningLLMs
- 114
- LlamaFactory
- 8.9k
Open issues
- FineTuningLLMs
- 4
- LlamaFactory
- 1.1k
Language
- FineTuningLLMs
- Jupyter Notebook
- LlamaFactory
- Python
Adopt for
- FineTuningLLMs
- -
- LlamaFactory
- LlamaFactory is a sophisticated tool for fine-tuning numerous large language models and visual language models efficiently using various methods such as LoRA, QLoRA, RLHF, and quantization.
Persona
- FineTuningLLMs
- -
- LlamaFactory
- -
Runtime
- FineTuningLLMs
- -
- LlamaFactory
- -
License
- FineTuningLLMs
- MIT
- LlamaFactory
- Apache-2.0
Last pushed
- FineTuningLLMs
- Feb 28, 2026
- LlamaFactory
- Jul 10, 2026
Categories
- FineTuningLLMs
- Inference & Serving, LLM Frameworks, Model Training
- LlamaFactory
- LLM Frameworks, Model Training
Trust and health
Maintenance
- FineTuningLLMs
- Slowing (36%)
- LlamaFactory
- Very active (96%)
Days since push
- FineTuningLLMs
- 132d
- LlamaFactory
- 0d
Open issues (now)
- FineTuningLLMs
- 4
- LlamaFactory
- 1.1k
Full report
- FineTuningLLMs
- Trust report
- LlamaFactory
- Trust report
Choose FineTuningLLMs if…
- FineTuningLLMs is primarily Jupyter Notebook; LlamaFactory is Python.
- License: FineTuningLLMs is MIT, LlamaFactory is Apache-2.0.
- Tags unique to FineTuningLLMs: bitsandbytes, finetuning, finetuning-llms, hugging-face.
- Also covers Inference & Serving.
When NOT to use FineTuningLLMs
- Last GitHub push was 133 days ago (slowing maintenance, Feb 28, 2026). Validate activity before betting a new project on FineTuningLLMs.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Choose LlamaFactory if…
- LlamaFactory is primarily Python; FineTuningLLMs is Jupyter Notebook.
- License: LlamaFactory is Apache-2.0, FineTuningLLMs is MIT.
- Tags unique to LlamaFactory: agent, ai, deepseek, gemma.
- When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA.
When NOT to use LlamaFactory
- When you are looking to fine-tune less popular or niche models that are not supported within the 100+ models covered by LlamaFactory.
- If your project specifically requires custom fine-tuning methods not available in this repository, such as certain versions of PEFT (Parameter Efficient Fine-Tuning) techniques excluding LoRA and QLoa
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 Jul 11, 2026
- GitHub forks (dvgodoy/FineTuningLLMs) · observed Jul 11, 2026
- Last push (dvgodoy/FineTuningLLMs) · observed Feb 28, 2026
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (hiyouga/LlamaFactory) · observed Jul 11, 2026
- GitHub forks (hiyouga/LlamaFactory) · observed Jul 11, 2026
- Last push (hiyouga/LlamaFactory) · observed Jul 10, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: FineTuningLLMs 848 · LlamaFactory 73k (synced Jul 11, 2026).
Common questions
- What is the difference between FineTuningLLMs and LlamaFactory?
- FineTuningLLMs: Official repository of my book "A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face". LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. See the comparison table for live GitHub stats and shared categories.
- When should I choose FineTuningLLMs over LlamaFactory?
- Choose FineTuningLLMs over LlamaFactory when FineTuningLLMs is primarily Jupyter Notebook; LlamaFactory is Python; License: FineTuningLLMs is MIT, LlamaFactory is Apache-2.0; Tags unique to FineTuningLLMs: bitsandbytes, finetuning, finetuning-llms, hugging-face; Also covers Inference & Serving.
- When should I choose LlamaFactory over FineTuningLLMs?
- Choose LlamaFactory over FineTuningLLMs when LlamaFactory is primarily Python; FineTuningLLMs is Jupyter Notebook; License: LlamaFactory is Apache-2.0, FineTuningLLMs is MIT; Tags unique to LlamaFactory: agent, ai, deepseek, gemma; When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA.
- When should I avoid FineTuningLLMs?
- Last GitHub push was 133 days ago (slowing maintenance, Feb 28, 2026). Validate activity before betting a new project on FineTuningLLMs. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- When should I avoid LlamaFactory?
- When you are looking to fine-tune less popular or niche models that are not supported within the 100+ models covered by LlamaFactory. If your project specifically requires custom fine-tuning methods not available in this repository, such as certain versions of PEFT (Parameter Efficient Fine-Tuning) techniques excluding LoRA and QLoa
- Is FineTuningLLMs or LlamaFactory more popular on GitHub?
- LlamaFactory has more GitHub stars (73,157 vs 848). Stars measure visibility, not whether either tool fits your constraints.
- Are FineTuningLLMs and LlamaFactory open source?
- Yes - both are open-source projects on GitHub (FineTuningLLMs: MIT, LlamaFactory: Apache-2.0).
- Where can I find alternatives to FineTuningLLMs or LlamaFactory?
- GraphCanon lists graph-backed alternatives at FineTuningLLMs alternatives and LlamaFactory alternatives (FineTuningLLMs markdown twin, LlamaFactory 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 LlamaFactory?
- FineTuningLLMs: Slowing. LlamaFactory: Very active. 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 LlamaFactory?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: FineTuningLLMs trust report; LlamaFactory trust report.