---
title: "FineTuningLLMs vs LLM-RLHF-Tuning"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/dvgodoy-finetuningllms-vs-joyce94-llm-rlhf-tuning"
tools: ["dvgodoy-finetuningllms", "joyce94-llm-rlhf-tuning"]
---

# FineTuningLLMs vs LLM-RLHF-Tuning

*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 LLM-RLHF-Tuning if framework for tuning large language models with PEFT & LoRA techniques like SFT, RM, PPO, DPO.

[FineTuningLLMs](https://github.com/dvgodoy/FineTuningLLMs) reports 855 GitHub stars, 116 forks, and 4 open issues, last pushed Feb 28, 2026. [LLM-RLHF-Tuning](https://github.com/Joyce94/LLM-RLHF-Tuning) has 452 stars, 24 forks, and 3 open issues, last pushed Oct 11, 2023. Figures are from public GitHub metadata via [FineTuningLLMs's repository](https://github.com/dvgodoy/FineTuningLLMs) and [LLM-RLHF-Tuning's repository](https://github.com/Joyce94/LLM-RLHF-Tuning).

| | [FineTuningLLMs](/tools/dvgodoy-finetuningllms.md) | [LLM-RLHF-Tuning](/tools/joyce94-llm-rlhf-tuning.md) |
| --- | --- | --- |
| Tagline | Official repository for 'A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face' | LLM Tuning with PEFT (SFT+RM+PPO+DPO with LoRA) |
| Stars | 855 | 452 |
| Forks | 116 | 24 |
| Open issues | 4 | 3 |
| Language | Jupyter Notebook | Python |
| Adopt for | FineTuningLLMs is designed for users familiar with PyTorch and Hugging Face who seek practical guidance via Jupyter Notebooks. | Framework for tuning large language models with PEFT & LoRA techniques like SFT, RM, PPO, DPO. |
| Persona | - | - |
| Runtime | - | - |
| License | MIT | - |
| 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) | [LLM-RLHF-Tuning](/tools/joyce94-llm-rlhf-tuning.md) |
| --- | --- | --- |
| Maintenance | Slowing (36%) | Dormant (18%) |
| Days since push | 176d | 1048d |
| Open issues (now) | 4 | 3 |
| Stars delta | +4 (30d) | -1 (30d) |
| Full report | [trust report](/tools/dvgodoy-finetuningllms/trust.md) | [trust report](/tools/joyce94-llm-rlhf-tuning/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: LLM-RLHF-Tuning

- **Adopt for:** Framework for tuning large language models with PEFT & LoRA techniques like SFT, RM, PPO, DPO.

## Choose when

### Choose FineTuningLLMs if…

- FineTuningLLMs is primarily Jupyter Notebook; LLM-RLHF-Tuning is Python.
- 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 LLM-RLHF-Tuning if…

- LLM-RLHF-Tuning is primarily Python; FineTuningLLMs is Jupyter Notebook.
- Tags unique to LLM-RLHF-Tuning: language-model, llama, llm, peft.
- When you need to fine-tune LLMS using PEFT methods such as SFT+RM+PPO+DPO alongside LoRA.

## When NOT to use FineTuningLLMs

- Not interested in PyTorch; prefer TensorFlow or another framework
- Seek theoretical background over practical applications

## When NOT to use LLM-RLHF-Tuning

- Avoid if your project only requires basic finetuning without the need for advanced techniques like PEFT or LoRA.
- Not suitable if you require a tool that supports other specific fine-tuning methods not covered by this framework.

## Common questions

### What is the difference between FineTuningLLMs and LLM-RLHF-Tuning?

FineTuningLLMs: Official repository for 'A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face'. LLM-RLHF-Tuning: LLM Tuning with PEFT (SFT+RM+PPO+DPO with LoRA). See the comparison table for live GitHub stats and shared categories.

### When should I choose FineTuningLLMs over LLM-RLHF-Tuning?

Choose FineTuningLLMs over LLM-RLHF-Tuning when FineTuningLLMs is primarily Jupyter Notebook; LLM-RLHF-Tuning is Python; 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 LLM-RLHF-Tuning over FineTuningLLMs?

Choose LLM-RLHF-Tuning over FineTuningLLMs when LLM-RLHF-Tuning is primarily Python; FineTuningLLMs is Jupyter Notebook; Tags unique to LLM-RLHF-Tuning: language-model, llama, llm, peft; When you need to fine-tune LLMS using PEFT methods such as SFT+RM+PPO+DPO alongside LoRA.

### When should I avoid FineTuningLLMs?

Not interested in PyTorch; prefer TensorFlow or another framework Seek theoretical background over practical applications

### When should I avoid LLM-RLHF-Tuning?

Avoid if your project only requires basic finetuning without the need for advanced techniques like PEFT or LoRA. Not suitable if you require a tool that supports other specific fine-tuning methods not covered by this framework.

### Is FineTuningLLMs or LLM-RLHF-Tuning more popular on GitHub?

FineTuningLLMs has more GitHub stars (855 vs 452). Stars measure visibility, not whether either tool fits your constraints.

### Are FineTuningLLMs and LLM-RLHF-Tuning open source?

Yes - both are open-source projects on GitHub.

### Where can I find alternatives to FineTuningLLMs or LLM-RLHF-Tuning?

GraphCanon lists graph-backed alternatives at [FineTuningLLMs alternatives](/tools/dvgodoy-finetuningllms/alternatives) and [LLM-RLHF-Tuning alternatives](/tools/joyce94-llm-rlhf-tuning/alternatives) ([FineTuningLLMs markdown twin](/tools/dvgodoy-finetuningllms/alternatives.md), [LLM-RLHF-Tuning markdown twin](/tools/joyce94-llm-rlhf-tuning/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-joyce94-llm-rlhf-tuning.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, FineTuningLLMs or LLM-RLHF-Tuning?

FineTuningLLMs: Slowing. LLM-RLHF-Tuning: 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 LLM-RLHF-Tuning?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FineTuningLLMs trust report](/tools/dvgodoy-finetuningllms/trust); [LLM-RLHF-Tuning trust report](/tools/joyce94-llm-rlhf-tuning/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/_