---
title: "LLMs-from-scratch vs EasyEdit"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/rasbt-llms-from-scratch-vs-zjunlp-easyedit"
tools: ["rasbt-llms-from-scratch", "zjunlp-easyedit"]
---

# LLMs-from-scratch vs EasyEdit

*GraphCanon updated Jul 11, 2026*

## Verdict

Pick LLMs-from-scratch when license: LLMs-from-scratch is Other, EasyEdit is MIT; pick EasyEdit when license: EasyEdit is MIT, LLMs-from-scratch is Other.

[LLMs-from-scratch](https://amzn.to/4fqvn0D) reports 99k GitHub stars, 15k forks, and 4 open issues, last pushed Jun 2, 2026. [EasyEdit](https://zjunlp.github.io/project/KnowEdit) has 2.9k stars, 370 forks, and 0 open issues, last pushed Jul 9, 2026. Figures are from public GitHub metadata via [LLMs-from-scratch's repository](https://github.com/rasbt/LLMs-from-scratch) and [EasyEdit's repository](https://github.com/zjunlp/EasyEdit).

| | [LLMs-from-scratch](/tools/rasbt-llms-from-scratch.md) | [EasyEdit](/tools/zjunlp-easyedit.md) |
| --- | --- | --- |
| Tagline | Implement a ChatGPT-like LLM in PyTorch from scratch, step by step | [ACL 2024] An Easy-to-use Knowledge Editing Framework for LLMs. |
| Stars | 98,899 | 2,868 |
| Forks | 15,183 | 370 |
| Open issues | 4 | 0 |
| Language | Jupyter Notebook | Jupyter Notebook |
| Adopt for | LLMs-from-scratch is a project-oriented repository aimed at building PyTorch-based language models from the ground up, with detailed step-by-step instructions. | - |
| Persona | - | - |
| Runtime | - | - |
| License | Other | MIT |
| Categories | LLM Frameworks, Model Training | Model Training, LLM Frameworks |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [LLMs-from-scratch](/tools/rasbt-llms-from-scratch.md) | [EasyEdit](/tools/zjunlp-easyedit.md) |
| --- | --- | --- |
| Maintenance | Steady (60%) | Very active (96%) |
| Days since push | 38d | 2d |
| Open issues (now) | 4 | 0 |
| Owner type | User | Organization |
| Security scan | No lockfile | 25 low (25 low) |
| Full report | [trust report](/tools/rasbt-llms-from-scratch/trust.md) | [trust report](/tools/zjunlp-easyedit/trust.md) |

## Decision facts: LLMs-from-scratch

- **Adopt for:** LLMs-from-scratch is a project-oriented repository aimed at building PyTorch-based language models from the ground up, with detailed step-by-step instructions.

## Choose when

### Choose LLMs-from-scratch if…

- License: LLMs-from-scratch is Other, EasyEdit is MIT.
- Tags unique to LLMs-from-scratch: deep-learning, ai, attention-mechanism, from-scratch.
- - You are an advanced practitioner aiming to fully understand the underpinnings of LLMs using PyTorch as your primary framework.

### Choose EasyEdit if…

- License: EasyEdit is MIT, LLMs-from-scratch is Other.
- Tags unique to EasyEdit: efficient, easyedit2, baichuan, easyedit.
- EasyEdit ships Docker support for self-hosted deployment.

## When NOT to use LLMs-from-scratch

- - If you are looking for a rapid deployment of an LLM without understanding its intricate structure - this tool requires extensive manual and conceptual work.
- - You prefer frameworks with automatic model generation or other high-level abstractions that simplify the process. This repository emphasizes manual creation, which is more time-consuming but offers丰
- a deeper learning experience.

## When NOT to use EasyEdit

- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

## Common questions

### What is the difference between LLMs-from-scratch and EasyEdit?

LLMs-from-scratch: Implement a ChatGPT-like LLM in PyTorch from scratch, step by step. EasyEdit: [ACL 2024] An Easy-to-use Knowledge Editing Framework for LLMs.. See the comparison table for live GitHub stats and shared categories.

### When should I choose LLMs-from-scratch over EasyEdit?

Choose LLMs-from-scratch over EasyEdit when License: LLMs-from-scratch is Other, EasyEdit is MIT; Tags unique to LLMs-from-scratch: deep-learning, ai, attention-mechanism, from-scratch; - You are an advanced practitioner aiming to fully understand the underpinnings of LLMs using PyTorch as your primary framework.

### When should I choose EasyEdit over LLMs-from-scratch?

Choose EasyEdit over LLMs-from-scratch when License: EasyEdit is MIT, LLMs-from-scratch is Other; Tags unique to EasyEdit: efficient, easyedit2, baichuan, easyedit; EasyEdit ships Docker support for self-hosted deployment.

### When should I avoid LLMs-from-scratch?

- If you are looking for a rapid deployment of an LLM without understanding its intricate structure - this tool requires extensive manual and conceptual work. - You prefer frameworks with automatic model generation or other high-level abstractions that simplify the process. This repository emphasizes manual creation, which is more time-consuming but offers丰 a deeper learning experience.

### When should I avoid EasyEdit?

Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

### Is LLMs-from-scratch or EasyEdit more popular on GitHub?

LLMs-from-scratch has more GitHub stars (98,899 vs 2,868). Stars measure visibility, not whether either tool fits your constraints.

### Are LLMs-from-scratch and EasyEdit open source?

Yes - both are open-source projects on GitHub (LLMs-from-scratch: Other, EasyEdit: MIT).

### Where can I find alternatives to LLMs-from-scratch or EasyEdit?

GraphCanon lists graph-backed alternatives at [LLMs-from-scratch alternatives](/tools/rasbt-llms-from-scratch/alternatives) and [EasyEdit alternatives](/tools/zjunlp-easyedit/alternatives) ([LLMs-from-scratch markdown twin](/tools/rasbt-llms-from-scratch/alternatives.md), [EasyEdit markdown twin](/tools/zjunlp-easyedit/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/rasbt-llms-from-scratch-vs-zjunlp-easyedit.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, LLMs-from-scratch or EasyEdit?

LLMs-from-scratch: Steady. EasyEdit: 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 LLMs-from-scratch and EasyEdit?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LLMs-from-scratch trust report](/tools/rasbt-llms-from-scratch/trust); [EasyEdit trust report](/tools/zjunlp-easyedit/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=rasbt-llms-from-scratch`](/api/graphcanon/graph?tool=rasbt-llms-from-scratch)
- 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/_
