Comparison
PiSSA vs superpipe
Verdict
Pick PiSSA if piSSA targets efficient fine-tuning of large language models via principal singular values and vectors; pick superpipe if superpipe specializes in optimizing large language model pipelines for tasks involving structured data such as classification and extraction.
Markdown twin · PiSSA alternatives · superpipe alternatives
GraphCanon updated today
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Trust & integrity
| Signal | PiSSA | superpipe |
|---|---|---|
| Maintenance | Dormant (420d since push) As of today · github_public_v1 | Dormant (770d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Organization account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) 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
- PiSSA
- Principal Singular Values and Singular Vectors Adaptation of Large Language Models
- superpipe
- Optimized LLM pipelines for structured data
Stars
- PiSSA
- 430
- superpipe
- 109
Forks
- PiSSA
- 23
- superpipe
- 2
Open issues
- PiSSA
- 16
- superpipe
- 3
Language
- PiSSA
- Jupyter Notebook
- superpipe
- Python
Adopt for
- PiSSA
- PiSSA targets efficient fine-tuning of large language models via principal singular values and vectors.
- superpipe
- Superpipe specializes in optimizing large language model pipelines for tasks involving structured data such as classification and extraction.
Persona
- PiSSA
- -
- superpipe
- -
Runtime
- PiSSA
- -
- superpipe
- -
License
- PiSSA
- -
- superpipe
- The license terms are under MIT, allowing for broad use and modification with attribution requirements maintained as per typical open-source licensing standards.
Last pushed
- PiSSA
- Jun 30, 2025
- superpipe
- Jun 18, 2024
Categories
- PiSSA
- LLM Frameworks, Model Training
- superpipe
- Data & Retrieval, LLM Frameworks, Model Training
Trust and health
Days since push
- PiSSA
- 420d
- superpipe
- 770d
Open issues (now)
- PiSSA
- 16
- superpipe
- 3
Stars delta
- PiSSA
- +1 (30d)
- superpipe
- Unknown
Open issues delta
- PiSSA
- 0 (30d)
- superpipe
- Unknown
OSV dependency advisories
- PiSSA
- No lockfile (source not queried)
- superpipe
- Published findings
Full report
- PiSSA
- Trust report
- superpipe
- Trust report
Choose PiSSA if…
- PiSSA is primarily Jupyter Notebook; superpipe is Python.
- Tags unique to PiSSA: fine-tuning, peft, quantization.
- You need to fine-tune a large language model efficiently with limited resources.
When NOT to use PiSSA
- Insufficient flexibility in model adaptation is acceptable, prefer broader customization options.
- Full fine-tuning of the entire model rather than just key components via peft.
Choose superpipe if…
- superpipe is primarily Python; PiSSA is Jupyter Notebook.
- Pricing: Superpipe is free to use under its MIT License for both commercial and non-commercial purposes, supporting a community-driven model with potential premium services or support options..
- Requirements: The minimum Python version required is 3.10+, as specified in the installation section..
- Tags unique to superpipe: classification, data-extraction, data-labeling, llm-optimization.
- Also covers Data & Retrieval.
- When you have specific tasks requiring the processing of structured datasets, such as detailed classification or precise data extraction.
When NOT to use superpipe
- If your project focuses on unstructured data mainly like free-form text analysis without a need for specialized structured-data algorithms.
- When the Python version requirement of at least 3.10 is not feasible in your development environment or dependencies.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (MuLabPKU/PiSSA) · observed Aug 24, 2026
- GitHub forks (MuLabPKU/PiSSA) · observed Aug 24, 2026
- Last push (MuLabPKU/PiSSA) · observed Jun 30, 2025
- License file (unknown) · observed Aug 24, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (villagecomputing/superpipe) · observed Jul 29, 2026
- GitHub forks (villagecomputing/superpipe) · observed Jul 29, 2026
- Last push (villagecomputing/superpipe) · observed Jun 18, 2024
- License file (unknown) · observed Jul 29, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: PiSSA 430 · superpipe 109 (synced Aug 24, 2026).
Common questions
- What is the difference between PiSSA and superpipe?
- PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models. superpipe: Optimized LLM pipelines for structured data. See the comparison table for live GitHub stats and shared categories.
- When should I choose PiSSA over superpipe?
- Choose PiSSA over superpipe when PiSSA is primarily Jupyter Notebook; superpipe is Python; Tags unique to PiSSA: fine-tuning, peft, quantization; You need to fine-tune a large language model efficiently with limited resources.
- When should I choose superpipe over PiSSA?
- Choose superpipe over PiSSA when superpipe is primarily Python; PiSSA is Jupyter Notebook; Pricing: Superpipe is free to use under its MIT License for both commercial and non-commercial purposes, supporting a community-driven model with potential premium services or support options.; Requirements: The minimum Python version required is 3.10+, as specified in the installation section.; Tags unique to superpipe: classification, data-extraction, data-labeling, llm-optimization; Also covers Data & Retrieval; When you have specific tasks requiring the processing of structured datasets, such as detailed classification or precise data extraction.
- When should I avoid PiSSA?
- Insufficient flexibility in model adaptation is acceptable, prefer broader customization options. Full fine-tuning of the entire model rather than just key components via peft.
- When should I avoid superpipe?
- If your project focuses on unstructured data mainly like free-form text analysis without a need for specialized structured-data algorithms. When the Python version requirement of at least 3.10 is not feasible in your development environment or dependencies.
- Is PiSSA or superpipe more popular on GitHub?
- PiSSA has more GitHub stars (430 vs 109). Stars measure visibility, not whether either tool fits your constraints.
- Are PiSSA and superpipe open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to PiSSA or superpipe?
- GraphCanon lists graph-backed alternatives at PiSSA alternatives and superpipe alternatives (PiSSA markdown twin, superpipe 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, PiSSA or superpipe?
- PiSSA: Dormant. superpipe: 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 PiSSA and superpipe?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: PiSSA trust report; superpipe trust report.