Comparison
Hands-On-Large-Language-Models vs CodeGeeX
Verdict
Pick Hands-On-Large-Language-Models if hands-On-Large-Language-Models offers code examples and educational content for large language models, as detailed in the O'Reilly book 'Hands-On Large Language Models'. The repository is in Jupyter Notebook format and,遵; pick CodeGeeX if codeGeeX is an open-source multilingual code generation model that supports both Mindspore and PyTorch frameworks, making it suitable for developers working with Ascend 910 AI.
Markdown twin · Hands-On-Large-Language-Models alternatives · CodeGeeX alternatives
GraphCanon updated Sep 20, 2026
8views this month
vs
Trust & integrity
| Signal | Hands-On-Large-Language-Models | CodeGeeX |
|---|---|---|
| Maintenance | Slowing (146d since push) As of Sep 18, 2026 · github_public_v1 | Dormant (766d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Sep 18, 2026 · osv@v1 | Published findings As of Sep 18, 2026 · 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
- Code for the book 'Hands-On Large Language Models'
- CodeGeeX
- CodeGeeX: An Open Multilingual Code Generation Model
Stars
- Hands-On-Large-Language-Models
- 29k
- CodeGeeX
- 8.8k
Forks
- Hands-On-Large-Language-Models
- 6.7k
- CodeGeeX
- 686
Open issues
- Hands-On-Large-Language-Models
- 40
- CodeGeeX
- 189
Language
- Hands-On-Large-Language-Models
- Jupyter Notebook
- CodeGeeX
- Python
Adopt for
- Hands-On-Large-Language-Models
- Hands-On-Large-Language-Models offers code examples and educational content for large language models, as detailed in the O'Reilly book 'Hands-On Large Language Models'. The repository is in Jupyter Notebook format and,遵
- CodeGeeX
- CodeGeeX is an open-source multilingual code generation model that supports both Mindspore and PyTorch frameworks, making it suitable for developers working with Ascend 910 AI Processors or GPU platforms.
Persona
- Hands-On-Large-Language-Models
- -
- CodeGeeX
- -
Runtime
- Hands-On-Large-Language-Models
- -
- CodeGeeX
- -
License
- Hands-On-Large-Language-Models
- Apache-2.0
- CodeGeeX
- CodeGeeX is licensed under the Apache-2.0 license, allowing for broad use, modification, and distribution of the code, while the model itself is under a separate license.
Last pushed
- Hands-On-Large-Language-Models
- Apr 24, 2026
- CodeGeeX
- Aug 13, 2024
Categories
- Hands-On-Large-Language-Models
- Developer Tools, LLM Frameworks
- CodeGeeX
- LLM Frameworks, Model Training
Trust and health
Maintenance
- Hands-On-Large-Language-Models
- Slowing (36%)
- CodeGeeX
- Dormant (18%)
Days since push
- Hands-On-Large-Language-Models
- 146d
- CodeGeeX
- 766d
Open issues (now)
- Hands-On-Large-Language-Models
- 40
- CodeGeeX
- 189
Stars delta
- Hands-On-Large-Language-Models
- +910 (30d)
- CodeGeeX
- -3 (30d)
Open issues delta
- Hands-On-Large-Language-Models
- +2 (30d)
- CodeGeeX
- +1 (30d)
Full report
- Hands-On-Large-Language-Models
- Trust report
- CodeGeeX
- Trust report
Choose Hands-On-Large-Language-Models if…
- Hands-On-Large-Language-Models is primarily Jupyter Notebook; CodeGeeX is Python.
- Tags unique to Hands-On-Large-Language-Models: artificial-intelligence, book, large-language-models, llm.
- Also covers Developer Tools.
- Use this tool if you are looking for practical, code-based learning resources that align with the book 'Hands-On Large Language Models'.
When NOT to use Hands-On-Large-Language-Models
- Avoid this tool if you are seeking a comprehensive theoretical background without practical examples, as the focus is on hands-on learning.
- Not recommended for users who prefer a different platform for running code examples, as the repository is optimized for Google Colab with a T4 GPU and 16GB VRAM.
- If you are looking for a tool that covers a broader range of AI topics beyond large language models, this repository may not be the best fit.
Choose CodeGeeX if…
- CodeGeeX is primarily Python; Hands-On-Large-Language-Models is Jupyter Notebook.
- Requirements: Requires Docker; Requires Python 3.7+, CUDA 11+, PyTorch 1.10+, and DeepSpeed 0.6+.; Supports installation via pip or through a Docker container for quick setup..
- Tags unique to CodeGeeX: code-generation, code-generation-model, gpu-support, mindspore.
- Also covers Model Training.
- When you need a multilingual code generation model that supports both Mindspore and PyTorch frameworks, allowing flexibility between Ascend 910 AI Processors and GPU platforms.
When NOT to use CodeGeeX
- If your project is strictly limited to TensorFlow or other frameworks not supported by CodeGeeX, as it primarily supports Mindspore and PyTorch.
- When your development environment does not support Python 3.7+, CUDA 11+, PyTorch 1.10+, or DeepSpeed 0.6+, as these are the minimum requirements for running CodeGeeX.
- If you are looking for a model that does not require specific hardware like Ascend 910 AI Processors or GPUs, as CodeGeeX is optimized for these platforms.
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 Sep 20, 2026
- GitHub forks (HandsOnLLM/Hands-On-Large-Language-Models) · observed Sep 20, 2026
- Last push (HandsOnLLM/Hands-On-Large-Language-Models) · observed Apr 24, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (zai-org/CodeGeeX) · observed Sep 20, 2026
- GitHub forks (zai-org/CodeGeeX) · observed Sep 20, 2026
- Last push (zai-org/CodeGeeX) · observed Aug 13, 2024
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: Hands-On-Large-Language-Models 29k · CodeGeeX 8.8k (synced Sep 20, 2026).
Common questions
- What is the difference between Hands-On-Large-Language-Models and CodeGeeX?
- Hands-On-Large-Language-Models: Code for the book 'Hands-On Large Language Models'. CodeGeeX: CodeGeeX: An Open Multilingual Code Generation Model. See the comparison table for live GitHub stats and shared categories.
- When should I choose Hands-On-Large-Language-Models over CodeGeeX?
- Choose Hands-On-Large-Language-Models over CodeGeeX when Hands-On-Large-Language-Models is primarily Jupyter Notebook; CodeGeeX is Python; Tags unique to Hands-On-Large-Language-Models: artificial-intelligence, book, large-language-models, llm; Also covers Developer Tools; Use this tool if you are looking for practical, code-based learning resources that align with the book 'Hands-On Large Language Models'.
- When should I choose CodeGeeX over Hands-On-Large-Language-Models?
- Choose CodeGeeX over Hands-On-Large-Language-Models when CodeGeeX is primarily Python; Hands-On-Large-Language-Models is Jupyter Notebook; Requirements: Requires Docker; Requires Python 3.7+, CUDA 11+, PyTorch 1.10+, and DeepSpeed 0.6+.; Supports installation via pip or through a Docker container for quick setup.; Tags unique to CodeGeeX: code-generation, code-generation-model, gpu-support, mindspore; Also covers Model Training; When you need a multilingual code generation model that supports both Mindspore and PyTorch frameworks, allowing flexibility between Ascend 910 AI Processors and GPU platforms.
- When should I avoid Hands-On-Large-Language-Models?
- Avoid this tool if you are seeking a comprehensive theoretical background without practical examples, as the focus is on hands-on learning. Not recommended for users who prefer a different platform for running code examples, as the repository is optimized for Google Colab with a T4 GPU and 16GB VRAM. If you are looking for a tool that covers a broader range of AI topics beyond large language models, this repository may not be the best fit.
- When should I avoid CodeGeeX?
- If your project is strictly limited to TensorFlow or other frameworks not supported by CodeGeeX, as it primarily supports Mindspore and PyTorch. When your development environment does not support Python 3.7+, CUDA 11+, PyTorch 1.10+, or DeepSpeed 0.6+, as these are the minimum requirements for running CodeGeeX. If you are looking for a model that does not require specific hardware like Ascend 910 AI Processors or GPUs, as CodeGeeX is optimized for these platforms.
- Is Hands-On-Large-Language-Models or CodeGeeX more popular on GitHub?
- Hands-On-Large-Language-Models has more GitHub stars (29,162 vs 8,806). Stars measure visibility, not whether either tool fits your constraints.
- Are Hands-On-Large-Language-Models and CodeGeeX open source?
- Yes - both are open-source projects on GitHub (Hands-On-Large-Language-Models: Apache-2.0, CodeGeeX: Apache-2.0).
- Where can I find alternatives to Hands-On-Large-Language-Models or CodeGeeX?
- GraphCanon lists graph-backed alternatives at Hands-On-Large-Language-Models alternatives and CodeGeeX alternatives (Hands-On-Large-Language-Models markdown twin, CodeGeeX 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 CodeGeeX?
- Hands-On-Large-Language-Models: Slowing. CodeGeeX: 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 Hands-On-Large-Language-Models and CodeGeeX?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Hands-On-Large-Language-Models trust report; CodeGeeX trust report.