Comparison
Hands-On-Large-Language-Models vs LLMs-from-scratch
Verdict
Pick Hands-On-Large-Language-Models if consider using the 'Hands-On-Large-Language-Models' repository if your interest aligns with hands-on learning and practice of large language models through coding examples; pick LLMs-from-scratch if 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.
Markdown twin · Hands-On-Large-Language-Models alternatives · LLMs-from-scratch alternatives
GraphCanon updated 3d
vs
Trust & integrity
| Signal | Hands-On-Large-Language-Models | LLMs-from-scratch |
|---|---|---|
| Maintenance | Slowing (114d since push) As of 3d · github_public_v1 | Very active (5d since push) As of 4d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3d · github_public_v1 | Not a fork · Personal account As of 4d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- Hands-On-Large-Language-Models
- Official code repo for the O'Reilly Book - 'Hands-On Large Language Models'
- LLMs-from-scratch
- Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Stars
- Hands-On-Large-Language-Models
- 28k
- LLMs-from-scratch
- 103k
Forks
- Hands-On-Large-Language-Models
- 6.5k
- LLMs-from-scratch
- 16k
Open issues
- Hands-On-Large-Language-Models
- 38
- LLMs-from-scratch
- 2
Language
- Hands-On-Large-Language-Models
- Jupyter Notebook
- LLMs-from-scratch
- Jupyter Notebook
Adopt for
- Hands-On-Large-Language-Models
- Consider using the 'Hands-On-Large-Language-Models' repository if your interest aligns with hands-on learning and practice of large language models through coding examples.
- 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.
Persona
- Hands-On-Large-Language-Models
- -
- LLMs-from-scratch
- -
Runtime
- Hands-On-Large-Language-Models
- -
- LLMs-from-scratch
- -
License
- Hands-On-Large-Language-Models
- Apache-2.0 License
- LLMs-from-scratch
- Other
Last pushed
- Hands-On-Large-Language-Models
- Apr 24, 2026
- LLMs-from-scratch
- Aug 10, 2026
Categories
- Hands-On-Large-Language-Models
- LLM Frameworks, Model Training
- LLMs-from-scratch
- LLM Frameworks, Model Training
Trust and health
Maintenance
- Hands-On-Large-Language-Models
- Slowing (36%)
- LLMs-from-scratch
- Very active (96%)
Days since push
- Hands-On-Large-Language-Models
- 114d
- LLMs-from-scratch
- 5d
Open issues (now)
- Hands-On-Large-Language-Models
- 38
- LLMs-from-scratch
- 2
Stars delta
- Hands-On-Large-Language-Models
- +642 (30d)
- LLMs-from-scratch
- +3.5k (30d)
Open issues delta
- Hands-On-Large-Language-Models
- 0 (30d)
- LLMs-from-scratch
- -1 (30d)
Owner type
- Hands-On-Large-Language-Models
- Organization
- LLMs-from-scratch
- User
Full report
- Hands-On-Large-Language-Models
- Trust report
- LLMs-from-scratch
- Trust report
Typed relationship
Hands-On-Large-Language-Models alternative LLMs-from-scratchBoth repositories are focused on hands-on tutorials and implementation of large language models, although 'Hands-On-Large-Language-Models' might provide a broader range of content as it is associated with an O'Reilly book.
Choose Hands-On-Large-Language-Models if…
- License: Hands-On-Large-Language-Models is Apache-2.0, LLMs-from-scratch is Other.
- Pricing: The repository is free and open under the Apache-2.0 license..
- Requirements: - Access to Jupyter Notebook is required for running code examples provided in this repository.; - Fundamental understanding of large language models and familiarity with AI concepts would be beneficial..
- Both repositories are focused on hands-on tutorials and implementation of large language models, although 'Hands-On-Large-Language-Models' might provide a broader range of content as it is associated with an O'Reilly book.
- Tags unique to Hands-On-Large-Language-Models: book, large language models, llm, llms.
- - You are focusing on practical implementation aspects detailed in a structured format as outlined by O'Reilly's authoritative book.
When NOT to use Hands-On-Large-Language-Models
- - If you need real-time model evaluation tools rather than educational materials, as this repository primarily provides code for understanding and implementing concepts covered in a book.
- - You are seeking proprietary or more specialized frameworks that go beyond the examples provided in an educational context to meet specific, advanced use-case needs.
Choose LLMs-from-scratch if…
- License: LLMs-from-scratch is Other, Hands-On-Large-Language-Models is Apache-2.0.
- Both repositories are focused on hands-on tutorials and implementation of large language models, although 'Hands-On-Large-Language-Models' might provide a broader range of content as it is associated with an O'Reilly book.
- Tags unique to LLMs-from-scratch: ai, attention-mechanism, deep-learning, finetuning.
- - 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
- a deeper learning experience.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (HandsOnLLM/Hands-On-Large-Language-Models) · observed Aug 16, 2026
- GitHub forks (HandsOnLLM/Hands-On-Large-Language-Models) · observed Aug 16, 2026
- Last push (HandsOnLLM/Hands-On-Large-Language-Models) · observed Apr 24, 2026
- License file (Apache-2.0) · observed Aug 16, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (rasbt/LLMs-from-scratch) · observed Aug 16, 2026
- GitHub forks (rasbt/LLMs-from-scratch) · observed Aug 16, 2026
- Last push (rasbt/LLMs-from-scratch) · observed Aug 10, 2026
- License file (Other) · observed Aug 16, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Hands-On-Large-Language-Models 28k · LLMs-from-scratch 103k (synced Aug 16, 2026).
Common questions
- What is the difference between Hands-On-Large-Language-Models and LLMs-from-scratch?
- Hands-On-Large-Language-Models: Official code repo for the O'Reilly Book - 'Hands-On Large Language Models'. LLMs-from-scratch: Implement a ChatGPT-like LLM in PyTorch from scratch, step by step. See the comparison table for live GitHub stats and shared categories.
- When should I choose Hands-On-Large-Language-Models over LLMs-from-scratch?
- Choose Hands-On-Large-Language-Models over LLMs-from-scratch when License: Hands-On-Large-Language-Models is Apache-2.0, LLMs-from-scratch is Other; Pricing: The repository is free and open under the Apache-2.0 license.; Requirements: - Access to Jupyter Notebook is required for running code examples provided in this repository.; - Fundamental understanding of large language models and familiarity with AI concepts would be beneficial.; Both repositories are focused on hands-on tutorials and implementation of large language models, although 'Hands-On-Large-Language-Models' might provide a broader range of content as it is associated with an O'Reilly book; Tags unique to Hands-On-Large-Language-Models: book, large language models, llm, llms; - You are focusing on practical implementation aspects detailed in a structured format as outlined by O'Reilly's authoritative book.
- When should I choose LLMs-from-scratch over Hands-On-Large-Language-Models?
- Choose LLMs-from-scratch over Hands-On-Large-Language-Models when License: LLMs-from-scratch is Other, Hands-On-Large-Language-Models is Apache-2.0; Both repositories are focused on hands-on tutorials and implementation of large language models, although 'Hands-On-Large-Language-Models' might provide a broader range of content as it is associated with an O'Reilly book; Tags unique to LLMs-from-scratch: ai, attention-mechanism, deep-learning, finetuning; - You are an advanced practitioner aiming to fully understand the underpinnings of LLMs using PyTorch as your primary framework.
- When should I avoid Hands-On-Large-Language-Models?
- - If you need real-time model evaluation tools rather than educational materials, as this repository primarily provides code for understanding and implementing concepts covered in a book. - You are seeking proprietary or more specialized frameworks that go beyond the examples provided in an educational context to meet specific, advanced use-case needs.
- 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 a deeper learning experience.
- Is Hands-On-Large-Language-Models or LLMs-from-scratch more popular on GitHub?
- LLMs-from-scratch has more GitHub stars (102,733 vs 28,252). Stars measure visibility, not whether either tool fits your constraints.
- Are Hands-On-Large-Language-Models and LLMs-from-scratch open source?
- Yes - both are open-source projects on GitHub (Hands-On-Large-Language-Models: Apache-2.0, LLMs-from-scratch: Other).
- Where can I find alternatives to Hands-On-Large-Language-Models or LLMs-from-scratch?
- GraphCanon lists graph-backed alternatives at Hands-On-Large-Language-Models alternatives and LLMs-from-scratch alternatives (Hands-On-Large-Language-Models markdown twin, LLMs-from-scratch 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, Hands-On-Large-Language-Models or LLMs-from-scratch?
- Hands-On-Large-Language-Models: Slowing. LLMs-from-scratch: 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 Hands-On-Large-Language-Models and LLMs-from-scratch?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Hands-On-Large-Language-Models trust report; LLMs-from-scratch trust report.