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Comparison

transformers vs prompt-patterns

Verdict

Pick transformers when requirements: Min 4 GB RAM; Works with Python 3.10+ and PyTorch 2.4+; pick prompt-patterns when tags unique to prompt-patterns: chatgpt, github-copilot, prompt-engineering, stable-diffusion.

Markdown twin · transformers alternatives · prompt-patterns alternatives

GraphCanon updated today

transformers logo

transformers

huggingface/transformers

★ 162kpushed Jul 11, 2026
vs
prompt-patterns logo

prompt-patterns

phodal/prompt-patterns

★ 3.1kpushed Mar 22, 2023

Trust & integrity

Signaltransformersprompt-patterns
Maintenance
Very active (0d since push)
As of 1d · github_public_v1
Dormant (1207d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of 1d · github_public_v1
Not a fork · Personal account
As of today · github_public_v1
Security (OSV)
No lockfile
As of 1d · none
No lockfile
As of today · none
transformers trust reportprompt-patterns trust reportTrust methodology

Tagline

transformers
Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models
prompt-patterns
Prompt 编写模式：如何将思维框架赋予机器，以设计模式的形式来思考 prompt

Stars

transformers
162k
prompt-patterns
3.1k

Forks

transformers
34k
prompt-patterns
198

Open issues

transformers
2.5k
prompt-patterns
0

Language

transformers
Python
prompt-patterns
-

Adopt for

transformers
Transformers is a versatile library for training and deploying state-of-the-art models across various domains such as NLP, computer vision, speech recognition, and multi-modal tasks. It supports PyTorch 2.4+ and Python 3
prompt-patterns
-

Persona

transformers
-
prompt-patterns
-

Runtime

transformers
-
prompt-patterns
-

License

transformers
Transformers is distributed under the Apache-2.0 license, ensuring wide permissions for use in both open-source and proprietary systems.
prompt-patterns
-

Last pushed

transformers
Jul 11, 2026
prompt-patterns
Mar 22, 2023

Categories

transformers
Computer Vision, Inference & Serving, LLM Frameworks, Model Training, Speech & Audio
prompt-patterns
Computer Vision, LLM Frameworks

Trust and health

Maintenance

transformers
Very active (96%)
prompt-patterns
Dormant (18%)

Days since push

transformers
0d
prompt-patterns
1207d

Open issues (now)

transformers
2.5k
prompt-patterns
0

Owner type

transformers
Organization
prompt-patterns
User

Full report

transformers
Trust report
prompt-patterns
Trust report

Choose transformers if…

  • Requirements: Min 4 GB RAM; Works with Python 3.10+ and PyTorch 2.4+.
  • Tags unique to transformers: audio, deep-learning, machine-learning, natural-language-processing.
  • Also covers Inference & Serving, Model Training, Speech & Audio.
  • The library excels in scenarios where you need highly optimized and pre-trained models available for a wide range of data types including text, vision, audio, and multimodal inputs.

When NOT to use transformers

  • If the specific task or dataset size does not benefit from state-of-the-art models due to computational inefficiency or overfitting, alternatives may be more suitable.
  • It might not be the best choice for projects that strictly require compatibility with frameworks other than PyTorch and Python versions older than 3.10.
GitHubDetails

Choose prompt-patterns if…

  • Tags unique to prompt-patterns: chatgpt, github-copilot, prompt-engineering, stable-diffusion.
  • Leaner open-issue backlog (0).

When NOT to use prompt-patterns

  • Last GitHub push was 1208 days ago (dormant maintenance, Mar 22, 2023). Validate activity before betting a new project on prompt-patterns.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
GitHubDetails

Explore

transformers trust report →prompt-patterns trust report →Computer Vision category →Inference & Serving category →LLM Frameworks category →Model Training category →Speech & Audio category →All comparisonsStack workflowsTrending tools

Sources

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

GitHub stars on cards: transformers 162k · prompt-patterns 3.1k (synced Jul 11, 2026).

Common questions

What is the difference between transformers and prompt-patterns?
transformers: Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models. prompt-patterns: Prompt 编写模式：如何将思维框架赋予机器，以设计模式的形式来思考 prompt. See the comparison table for live GitHub stats and shared categories.
When should I choose transformers over prompt-patterns?
Choose transformers over prompt-patterns when Requirements: Min 4 GB RAM; Works with Python 3.10+ and PyTorch 2.4+; Tags unique to transformers: audio, deep-learning, machine-learning, natural-language-processing; Also covers Inference & Serving, Model Training, Speech & Audio; The library excels in scenarios where you need highly optimized and pre-trained models available for a wide range of data types including text, vision, audio, and multimodal inputs.
When should I choose prompt-patterns over transformers?
Choose prompt-patterns over transformers when Tags unique to prompt-patterns: chatgpt, github-copilot, prompt-engineering, stable-diffusion; Leaner open-issue backlog (0).
When should I avoid transformers?
If the specific task or dataset size does not benefit from state-of-the-art models due to computational inefficiency or overfitting, alternatives may be more suitable. It might not be the best choice for projects that strictly require compatibility with frameworks other than PyTorch and Python versions older than 3.10.
When should I avoid prompt-patterns?
Last GitHub push was 1208 days ago (dormant maintenance, Mar 22, 2023). Validate activity before betting a new project on prompt-patterns. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Is transformers or prompt-patterns more popular on GitHub?
transformers has more GitHub stars (162,482 vs 3,095). Stars measure visibility, not whether either tool fits your constraints.
Are transformers and prompt-patterns open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to transformers or prompt-patterns?
GraphCanon lists graph-backed alternatives at transformers alternatives and prompt-patterns alternatives (transformers markdown twin, prompt-patterns 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, transformers or prompt-patterns?
transformers: Very active. prompt-patterns: 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 transformers and prompt-patterns?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: transformers trust report; prompt-patterns trust report.