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
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Trust & integrity
| Signal | LLMs-from-scratch | EasyEdit |
|---|---|---|
| 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 (rasbt/LLMs-from-scratch) · observed Jul 11, 2026
- GitHub forks (rasbt/LLMs-from-scratch) · observed Jul 11, 2026
- Last push (rasbt/LLMs-from-scratch) · observed Jun 2, 2026
- License file (Other) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (zjunlp/EasyEdit) · observed Jul 11, 2026
- GitHub forks (zjunlp/EasyEdit) · observed Jul 11, 2026
- Last push (zjunlp/EasyEdit) · observed Jul 9, 2026
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
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.