Comparison
accelerate vs hyperband
Verdict
Pick accelerate if tool: accelerate; pick hyperband if hyperband optimizes hyperparameters quickly with an efficient bandit-based approach, supporting several models from scikit-learn and polylearn.
Markdown twin · accelerate alternatives · hyperband alternatives
GraphCanon updated 3w
vs
Trust & integrity
| Signal | accelerate | hyperband |
|---|---|---|
| Maintenance | Very active (3d since push) As of 3w · github_public_v1 | Dormant (2910d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Personal account As of 3w · 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
- accelerate
- A tool for launching, training, and using PyTorch models with ease on various devices, configurations, including mixed precision support.
- hyperband
- Tuning hyperparams fast with Hyperband
Stars
- accelerate
- 9.8k
- hyperband
- 599
Forks
- accelerate
- 1.4k
- hyperband
- 73
Open issues
- accelerate
- 105
- hyperband
- 9
Language
- accelerate
- Python
- hyperband
- Python
Adopt for
- accelerate
- Tool: accelerate
- hyperband
- Hyperband optimizes hyperparameters quickly with an efficient bandit-based approach, supporting several models from scikit-learn and polylearn.
Persona
- accelerate
- -
- hyperband
- -
Runtime
- accelerate
- -
- hyperband
- -
License
- accelerate
- Apache-2.0
- hyperband
- Other
Last pushed
- accelerate
- Jul 30, 2026
- hyperband
- Aug 15, 2018
Categories
- accelerate
- Inference & Serving, Model Training
- hyperband
- Model Training
Trust and health
Maintenance
- accelerate
- Very active (96%)
- hyperband
- Dormant (18%)
Days since push
- accelerate
- 3d
- hyperband
- 2910d
Open issues (now)
- accelerate
- 105
- hyperband
- 9
Owner type
- accelerate
- Organization
- hyperband
- User
Full report
- accelerate
- Trust report
- hyperband
- Trust report
Shared compatibility
- Python · accelerate: Python runtime · hyperband: Python runtime
Choose accelerate if…
- License: accelerate is Apache-2.0, hyperband is Other.
- Tags unique to accelerate: deepspeed, fsdp, mixed precision, pytorch.
- Also covers Inference & Serving.
- Easy mixed-precision support for PyTorch models
When NOT to use accelerate
- Non-PyTorch projects do not benefit from this tool
- Doesnt offer advanced auto-tuning features for other frameworks like TensorFlow
- Limited to Python environments compatible with PyTorch 1.10.0+
Choose hyperband if…
- License: hyperband is Other, accelerate is Apache-2.0.
- Tags unique to hyperband: classification, gradient-boosting, hyperparameter-optimization, machine-learning.
- Use Hyperband when you need fast optimization of hyperparameters for classifiers such as gradient boosting or regressors like factorization machines from polylearn.
When NOT to use hyperband
- Avoid Hyperband if you require custom data formats that differ significantly from scikit-learn conventions, as this will necessitate extensive customization of the load_data modules.
- Do not use Hyperband when the models you need for hyperparameter tuning are not among the eight pre-supported models; additional support is required outside what comes built-in.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (huggingface/accelerate) · observed Aug 3, 2026
- GitHub forks (huggingface/accelerate) · observed Aug 3, 2026
- Last push (huggingface/accelerate) · observed Jul 30, 2026
- License file (Apache-2.0) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (zygmuntz/hyperband) · observed Aug 4, 2026
- GitHub forks (zygmuntz/hyperband) · observed Aug 4, 2026
- Last push (zygmuntz/hyperband) · observed Aug 15, 2018
- License file (Other) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: accelerate 9.8k · hyperband 599 (synced Aug 3, 2026).
Common questions
- What is the difference between accelerate and hyperband?
- accelerate: A tool for launching, training, and using PyTorch models with ease on various devices, configurations, including mixed precision support.. hyperband: Tuning hyperparams fast with Hyperband. See the comparison table for live GitHub stats and shared categories.
- When should I choose accelerate over hyperband?
- Choose accelerate over hyperband when License: accelerate is Apache-2.0, hyperband is Other; Tags unique to accelerate: deepspeed, fsdp, mixed precision, pytorch; Also covers Inference & Serving; Easy mixed-precision support for PyTorch models.
- When should I choose hyperband over accelerate?
- Choose hyperband over accelerate when License: hyperband is Other, accelerate is Apache-2.0; Tags unique to hyperband: classification, gradient-boosting, hyperparameter-optimization, machine-learning; Use Hyperband when you need fast optimization of hyperparameters for classifiers such as gradient boosting or regressors like factorization machines from polylearn.
- When should I avoid accelerate?
- Non-PyTorch projects do not benefit from this tool Doesnt offer advanced auto-tuning features for other frameworks like TensorFlow Limited to Python environments compatible with PyTorch 1.10.0+
- When should I avoid hyperband?
- Avoid Hyperband if you require custom data formats that differ significantly from scikit-learn conventions, as this will necessitate extensive customization of the load_data modules. Do not use Hyperband when the models you need for hyperparameter tuning are not among the eight pre-supported models; additional support is required outside what comes built-in.
- Is accelerate or hyperband more popular on GitHub?
- accelerate has more GitHub stars (9,803 vs 599). Stars measure visibility, not whether either tool fits your constraints.
- Are accelerate and hyperband open source?
- Yes - both are open-source projects on GitHub (accelerate: Apache-2.0, hyperband: Other).
- Where can I find alternatives to accelerate or hyperband?
- GraphCanon lists graph-backed alternatives at accelerate alternatives and hyperband alternatives (accelerate markdown twin, hyperband 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, accelerate or hyperband?
- accelerate: Very active. hyperband: 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 accelerate and hyperband?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: accelerate trust report; hyperband trust report.