Comparison
Awesome-Chinese-LLM vs Keras-TextClassification
Verdict
Pick Awesome-Chinese-LLM if awesome-Chinese-LLM is a curated list focusing on smaller, less computationally expensive Chinese language models suitable for private deployment; pick Keras-TextClassification if chinese-focused text classification models using Keras.
Markdown twin · Awesome-Chinese-LLM alternatives · Keras-TextClassification alternatives
GraphCanon updated 1d
vs
Trust & integrity
| Signal | Awesome-Chinese-LLM | Keras-TextClassification |
|---|---|---|
| Maintenance | Slowing (98d since push) As of 1w · github_public_v1 | Dormant (795d since push) As of 1d · github_public_v1 |
| Provenance | Not a fork · Personal account As of 1w · github_public_v1 | Not a fork · Personal account As of 1d · 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
- Awesome-Chinese-LLM
- 整理开源的中文大语言模型
- Keras-TextClassification
- Chinese text classification models based on Keras
Stars
- Awesome-Chinese-LLM
- 23k
- Keras-TextClassification
- 1.8k
Forks
- Awesome-Chinese-LLM
- 2.1k
- Keras-TextClassification
- 397
Open issues
- Awesome-Chinese-LLM
- 27
- Keras-TextClassification
- 4
Language
- Awesome-Chinese-LLM
- -
- Keras-TextClassification
- Python
Adopt for
- Awesome-Chinese-LLM
- Awesome-Chinese-LLM is a curated list focusing on smaller, less computationally expensive Chinese language models suitable for private deployment.
- Keras-TextClassification
- Chinese-focused text classification models using Keras.
Persona
- Awesome-Chinese-LLM
- -
- Keras-TextClassification
- -
Runtime
- Awesome-Chinese-LLM
- -
- Keras-TextClassification
- -
License
- Awesome-Chinese-LLM
- -
- Keras-TextClassification
- MIT License - allows free use, modification, distribution with attribution required but no guarantee or liability from contributors.
Last pushed
- Awesome-Chinese-LLM
- May 10, 2026
- Keras-TextClassification
- Jun 17, 2024
Categories
- Awesome-Chinese-LLM
- LLM Frameworks, Model Training
- Keras-TextClassification
- Model Training
Trust and health
Maintenance
- Awesome-Chinese-LLM
- Slowing (36%)
- Keras-TextClassification
- Dormant (18%)
Days since push
- Awesome-Chinese-LLM
- 98d
- Keras-TextClassification
- 795d
Open issues (now)
- Awesome-Chinese-LLM
- 27
- Keras-TextClassification
- 4
Stars delta
- Awesome-Chinese-LLM
- +53 (30d)
- Keras-TextClassification
- -3 (30d)
Open issues delta
- Awesome-Chinese-LLM
- +3 (30d)
- Keras-TextClassification
- 0 (30d)
Full report
- Awesome-Chinese-LLM
- Trust report
- Keras-TextClassification
- Trust report
Choose Awesome-Chinese-LLM if…
- Tags unique to Awesome-Chinese-LLM: awesome-lists, chatglm, chinese, llama.
- Also covers LLM Frameworks.
- If you are looking to implement low-cost and efficient Chinese NLP solutions that can be deployed privately.
When NOT to use Awesome-Chinese-LLM
- Avoid if your project necessitates large-scale, highly advanced computational capabilities or you are working with languages other than Chinese.
- If your deployment scenario is limited to public cloud services only without the option for private deployment.
Choose Keras-TextClassification if…
- Requirements: Min 4 GB RAM; Python environment must be prepared for running Keras.; Supports multiple model types requiring different levels of computation resources..
- Tags unique to Keras-TextClassification: albert, bert, capsulenetwork, charcnn.
- Requires Chinese text classification for tasks like multi-label, sentence similarity analysis.
When NOT to use Keras-TextClassification
- Does not cater to non-Chinese language datasets effectively due to its Chinese-specific models.
- Avoid if you seek a tool with extensive support beyond text classification like NER or POS tagging.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (AiHubCN/Awesome-Chinese-LLM) · observed Aug 17, 2026
- GitHub forks (AiHubCN/Awesome-Chinese-LLM) · observed Aug 17, 2026
- Last push (AiHubCN/Awesome-Chinese-LLM) · observed May 10, 2026
- License file (unknown) · observed Aug 17, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (yongzhuo/Keras-TextClassification) · observed Aug 22, 2026
- GitHub forks (yongzhuo/Keras-TextClassification) · observed Aug 22, 2026
- Last push (yongzhuo/Keras-TextClassification) · observed Jun 17, 2024
- License file (MIT) · observed Aug 22, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Awesome-Chinese-LLM 23k · Keras-TextClassification 1.8k (synced Aug 17, 2026).
Common questions
- What is the difference between Awesome-Chinese-LLM and Keras-TextClassification?
- Awesome-Chinese-LLM: 整理开源的中文大语言模型. Keras-TextClassification: Chinese text classification models based on Keras. See the comparison table for live GitHub stats and shared categories.
- When should I choose Awesome-Chinese-LLM over Keras-TextClassification?
- Choose Awesome-Chinese-LLM over Keras-TextClassification when Tags unique to Awesome-Chinese-LLM: awesome-lists, chatglm, chinese, llama; Also covers LLM Frameworks; If you are looking to implement low-cost and efficient Chinese NLP solutions that can be deployed privately.
- When should I choose Keras-TextClassification over Awesome-Chinese-LLM?
- Choose Keras-TextClassification over Awesome-Chinese-LLM when Requirements: Min 4 GB RAM; Python environment must be prepared for running Keras.; Supports multiple model types requiring different levels of computation resources.; Tags unique to Keras-TextClassification: albert, bert, capsulenetwork, charcnn; Requires Chinese text classification for tasks like multi-label, sentence similarity analysis.
- When should I avoid Awesome-Chinese-LLM?
- Avoid if your project necessitates large-scale, highly advanced computational capabilities or you are working with languages other than Chinese. If your deployment scenario is limited to public cloud services only without the option for private deployment.
- When should I avoid Keras-TextClassification?
- Does not cater to non-Chinese language datasets effectively due to its Chinese-specific models. Avoid if you seek a tool with extensive support beyond text classification like NER or POS tagging.
- Is Awesome-Chinese-LLM or Keras-TextClassification more popular on GitHub?
- Awesome-Chinese-LLM has more GitHub stars (22,738 vs 1,809). Stars measure visibility, not whether either tool fits your constraints.
- Are Awesome-Chinese-LLM and Keras-TextClassification open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to Awesome-Chinese-LLM or Keras-TextClassification?
- GraphCanon lists graph-backed alternatives at Awesome-Chinese-LLM alternatives and Keras-TextClassification alternatives (Awesome-Chinese-LLM markdown twin, Keras-TextClassification 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, Awesome-Chinese-LLM or Keras-TextClassification?
- Awesome-Chinese-LLM: Slowing. Keras-TextClassification: 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 Awesome-Chinese-LLM and Keras-TextClassification?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Awesome-Chinese-LLM trust report; Keras-TextClassification trust report.