Home/Compare/LLMs-from-scratch vs EasyEdit

Comparison

LLMs-from-scratch vs EasyEdit

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.

Markdown twin · LLMs-from-scratch alternatives · EasyEdit alternatives

GraphCanon updated today

LLMs-from-scratch logo

LLMs-from-scratch

rasbt/LLMs-from-scratch

99kpushed Jun 2, 2026
vs
EasyEdit logo

EasyEdit

zjunlp/EasyEdit

2.9kpushed Jul 9, 2026

Trust & integrity

SignalLLMs-from-scratchEasyEdit
Maintenance
Steady (38d since push)
As of today · github_public_v1
Very active (2d since push)
As of today · github_public_v1
Provenance
Not a fork · Personal account
As of today · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
25 low (25 low)
As of today · osv@v1

Tagline

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.

Stars

LLMs-from-scratch
99k
EasyEdit
2.9k

Forks

LLMs-from-scratch
15k
EasyEdit
370

Open issues

LLMs-from-scratch
4
EasyEdit
0

Language

LLMs-from-scratch
Jupyter Notebook
EasyEdit
Jupyter Notebook

Adopt for

LLMs-from-scratch
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.
EasyEdit
-

Persona

LLMs-from-scratch
-
EasyEdit
-

Runtime

LLMs-from-scratch
-
EasyEdit
-

License

LLMs-from-scratch
Other
EasyEdit
MIT

Last pushed

LLMs-from-scratch
Jun 2, 2026
EasyEdit
Jul 9, 2026

Categories

LLMs-from-scratch
Model Training, LLM Frameworks
EasyEdit
LLM Frameworks, Model Training

Trust and health

Maintenance

LLMs-from-scratch
Steady (60%)
EasyEdit
Very active (96%)

Days since push

LLMs-from-scratch
38d
EasyEdit
2d

Open issues (now)

LLMs-from-scratch
4
EasyEdit
0

Owner type

LLMs-from-scratch
User
EasyEdit
Organization

Security scan

LLMs-from-scratch
No lockfile
EasyEdit
25 low (25 low)

Full report

LLMs-from-scratch
Trust report
EasyEdit
Trust report

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.

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.

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 EasyEdit

  • 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.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: LLMs-from-scratch 99k · EasyEdit 2.9k (synced Jul 11, 2026).

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?
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.
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 and EasyEdit alternatives (LLMs-from-scratch markdown twin, EasyEdit 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, 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; EasyEdit trust report.