Comparison
alpaca-lora vs Chinese-LLaMA-Alpaca
Verdict
Pick alpaca-lora if alpaca-lora is an instruct tuning repository for the LLaMA model designed to work with consumer-grade hardware through Docker integration; pick Chinese-LLaMA-Alpaca if `Chinese-LLaMA-Alpaca` is a repository that includes Chinese versions of the LLaMA and Alpaca large language models, specifically designed with extended Chinese vocabulary and fine-tuned on Chinese instruction data for a.
Markdown twin · alpaca-lora alternatives · Chinese-LLaMA-Alpaca alternatives
GraphCanon updated 4d
vs
Trust & integrity
| Signal | alpaca-lora | Chinese-LLaMA-Alpaca |
|---|---|---|
| Maintenance | Dormant (734d since push) As of 2w · github_public_v1 | Slowing (119d since push) As of 4d · github_public_v1 |
| Provenance | Not a fork · Personal account As of 2w · github_public_v1 | Not a fork · Personal account As of 4d · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | Published findings 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
- alpaca-lora
- Instruct-tune LLaMA on consumer hardware
- Chinese-LLaMA-Alpaca
- Chinese LLaMA & Alpaca Large Language Models for Local CPU/GPU Training and Deployment
Stars
- alpaca-lora
- 19k
- Chinese-LLaMA-Alpaca
- 19k
Forks
- alpaca-lora
- 2.2k
- Chinese-LLaMA-Alpaca
- 1.8k
Open issues
- alpaca-lora
- 365
- Chinese-LLaMA-Alpaca
- 6
Language
- alpaca-lora
- Jupyter Notebook
- Chinese-LLaMA-Alpaca
- Python
Adopt for
- alpaca-lora
- alpaca-lora is an instruct tuning repository for the LLaMA model designed to work with consumer-grade hardware through Docker integration.
- Chinese-LLaMA-Alpaca
- `Chinese-LLaMA-Alpaca` is a repository that includes Chinese versions of the LLaMA and Alpaca large language models, specifically designed with extended Chinese vocabulary and fine-tuned on Chinese instruction data for a
Persona
- alpaca-lora
- developer harness
- Chinese-LLaMA-Alpaca
- -
Runtime
- alpaca-lora
- -
- Chinese-LLaMA-Alpaca
- -
License
- alpaca-lora
- The Apache-2.0 license applies, allowing wide-ranging reuse and distribution of the software, provided that copyright notices are included and applicable files accompany distributed executables.
- Chinese-LLaMA-Alpaca
- The repository is licensed under Apache-2.0 which allows you to use the content openly in both commercial and non-commercial projects provided you adhere to the licensing terms.
Last pushed
- alpaca-lora
- Jul 29, 2024
- Chinese-LLaMA-Alpaca
- Apr 19, 2026
Categories
- alpaca-lora
- Inference & Serving, LLM Frameworks, Model Training
- Chinese-LLaMA-Alpaca
- LLM Frameworks, Model Training
Trust and health
Maintenance
- alpaca-lora
- Dormant (18%)
- Chinese-LLaMA-Alpaca
- Slowing (36%)
Days since push
- alpaca-lora
- 734d
- Chinese-LLaMA-Alpaca
- 119d
Open issues (now)
- alpaca-lora
- 365
- Chinese-LLaMA-Alpaca
- 6
Stars delta
- alpaca-lora
- Unknown
- Chinese-LLaMA-Alpaca
- -9 (30d)
Open issues delta
- alpaca-lora
- Unknown
- Chinese-LLaMA-Alpaca
- 0 (30d)
Full report
- alpaca-lora
- Trust report
- Chinese-LLaMA-Alpaca
- Trust report
Choose alpaca-lora if…
- alpaca-lora is primarily Jupyter Notebook; Chinese-LLaMA-Alpaca is Python.
- Pricing: The source code is freely available under the Apache-2.0 license, but costs associated with hardware and cloud services for running Docker may apply..
- Tags unique to alpaca-lora: consumer hardware, docker, instruct-tune, lora.
- Also covers Inference & Serving.
- alpaca-lora ships Docker support for self-hosted deployment.
- When you have limited GPU resources but want to perform instruction-fine-tuning on the LLaMA model, and your setup supports basic Docker.
When NOT to use alpaca-lora
- When you require more advanced customization beyond what is offered through the `finetune.py` script parameters or Jupyter Notebook interface.
- For teams with high-performance computing resources aiming for optimal performance, as alpaca-lora is optimized for use on consumer-grade hardware.
Choose Chinese-LLaMA-Alpaca if…
- Chinese-LLaMA-Alpaca is primarily Python; alpaca-lora is Jupyter Notebook.
- Pricing: Access to `Chinese-LLaMA-Alpaca` models and documentation is free, but commercial usage should adhere to open-source licensing requirements..
- Tags unique to Chinese-LLaMA-Alpaca: alpaca, large language models, nlp, pre-trained-language-models.
- You should consider using `Chinese-LLaMA-Alpaca` if your project involves local deployment and training using CPUs or GPUs, particularly if the focus is on Chinese language texts. These models are pre
When NOT to use Chinese-LLaMA-Alpaca
- `Chinese-LLaMA-Alpaca` might not be the best fit if your project requires extensive multi-language support beyond Chinese.
- If you are exclusively targeting markets where English is the primary language, and fine-tuning or additional pre-training on Chinese data does not add value to your application.
- Avoid using this tool if you require a model that has been extensively trained across global datasets for broad international comprehension, as `Chinese-LLaMA-Alpaca` is focused heavily on Chinese.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (tloen/alpaca-lora) · observed Aug 3, 2026
- GitHub forks (tloen/alpaca-lora) · observed Aug 3, 2026
- Last push (tloen/alpaca-lora) · observed Jul 29, 2024
- License file (Apache-2.0) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (ymcui/Chinese-LLaMA-Alpaca) · observed Aug 17, 2026
- GitHub forks (ymcui/Chinese-LLaMA-Alpaca) · observed Aug 17, 2026
- Last push (ymcui/Chinese-LLaMA-Alpaca) · observed Apr 19, 2026
- License file (Apache-2.0) · observed Aug 17, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: alpaca-lora 19k · Chinese-LLaMA-Alpaca 19k (synced Aug 3, 2026).
Common questions
- What is the difference between alpaca-lora and Chinese-LLaMA-Alpaca?
- alpaca-lora: Instruct-tune LLaMA on consumer hardware. Chinese-LLaMA-Alpaca: Chinese LLaMA & Alpaca Large Language Models for Local CPU/GPU Training and Deployment. See the comparison table for live GitHub stats and shared categories.
- When should I choose alpaca-lora over Chinese-LLaMA-Alpaca?
- Choose alpaca-lora over Chinese-LLaMA-Alpaca when alpaca-lora is primarily Jupyter Notebook; Chinese-LLaMA-Alpaca is Python; Pricing: The source code is freely available under the Apache-2.0 license, but costs associated with hardware and cloud services for running Docker may apply.; Tags unique to alpaca-lora: consumer hardware, docker, instruct-tune, lora; Also covers Inference & Serving; alpaca-lora ships Docker support for self-hosted deployment; When you have limited GPU resources but want to perform instruction-fine-tuning on the LLaMA model, and your setup supports basic Docker.
- When should I choose Chinese-LLaMA-Alpaca over alpaca-lora?
- Choose Chinese-LLaMA-Alpaca over alpaca-lora when Chinese-LLaMA-Alpaca is primarily Python; alpaca-lora is Jupyter Notebook; Pricing: Access to
Chinese-LLaMA-Alpacamodels and documentation is free, but commercial usage should adhere to open-source licensing requirements.; Tags unique to Chinese-LLaMA-Alpaca: alpaca, large language models, nlp, pre-trained-language-models; You should consider usingChinese-LLaMA-Alpacaif your project involves local deployment and training using CPUs or GPUs, particularly if the focus is on Chinese language texts. These models are pre. - When should I avoid alpaca-lora?
- When you require more advanced customization beyond what is offered through the
finetune.pyscript parameters or Jupyter Notebook interface. For teams with high-performance computing resources aiming for optimal performance, as alpaca-lora is optimized for use on consumer-grade hardware. - When should I avoid Chinese-LLaMA-Alpaca?
Chinese-LLaMA-Alpacamight not be the best fit if your project requires extensive multi-language support beyond Chinese. If you are exclusively targeting markets where English is the primary language, and fine-tuning or additional pre-training on Chinese data does not add value to your application. Avoid using this tool if you require a model that has been extensively trained across global datasets for broad international comprehension, asChinese-LLaMA-Alpacais focused heavily on Chinese.- Is alpaca-lora or Chinese-LLaMA-Alpaca more popular on GitHub?
- Chinese-LLaMA-Alpaca has more GitHub stars (18,933 vs 18,912). Stars measure visibility, not whether either tool fits your constraints.
- Are alpaca-lora and Chinese-LLaMA-Alpaca open source?
- Yes - both are open-source projects on GitHub (alpaca-lora: Apache-2.0, Chinese-LLaMA-Alpaca: Apache-2.0).
- Where can I find alternatives to alpaca-lora or Chinese-LLaMA-Alpaca?
- GraphCanon lists graph-backed alternatives at alpaca-lora alternatives and Chinese-LLaMA-Alpaca alternatives (alpaca-lora markdown twin, Chinese-LLaMA-Alpaca 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, alpaca-lora or Chinese-LLaMA-Alpaca?
- alpaca-lora: Dormant. Chinese-LLaMA-Alpaca: Slowing. 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 alpaca-lora and Chinese-LLaMA-Alpaca?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: alpaca-lora trust report; Chinese-LLaMA-Alpaca trust report.