Comparison
accelerate vs DeepLearningExamples
Verdict
Pick accelerate if tool: accelerate; pick DeepLearningExamples if curated facts for DeepLearningExamples, tailored to its unique features and offerings.
Markdown twin · accelerate alternatives · DeepLearningExamples alternatives
GraphCanon updated 4d
vs
Trust & integrity
| Signal | accelerate | DeepLearningExamples |
|---|---|---|
| Maintenance | Very active (3d since push) As of 2w · github_public_v1 | Dormant (734d since push) As of 4d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 4d · 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.
- DeepLearningExamples
- State-of-the-Art Deep Learning scripts for various applications
Stars
- accelerate
- 9.8k
- DeepLearningExamples
- 15k
Forks
- accelerate
- 1.4k
- DeepLearningExamples
- 3.4k
Open issues
- accelerate
- 105
- DeepLearningExamples
- 321
Language
- accelerate
- Python
- DeepLearningExamples
- Jupyter Notebook
Adopt for
- accelerate
- Tool: accelerate
- DeepLearningExamples
- Curated facts for DeepLearningExamples, tailored to its unique features and offerings.
Persona
- accelerate
- -
- DeepLearningExamples
- -
Runtime
- accelerate
- -
- DeepLearningExamples
- -
License
- accelerate
- Apache-2.0
- DeepLearningExamples
- -
Last pushed
- accelerate
- Jul 30, 2026
- DeepLearningExamples
- Aug 12, 2024
Categories
- accelerate
- Inference & Serving, Model Training
- DeepLearningExamples
- Inference & Serving, Model Training
Trust and health
Maintenance
- accelerate
- Very active (96%)
- DeepLearningExamples
- Dormant (18%)
Days since push
- accelerate
- 3d
- DeepLearningExamples
- 734d
Open issues (now)
- accelerate
- 105
- DeepLearningExamples
- 321
Stars delta
- accelerate
- Unknown
- DeepLearningExamples
- +14 (30d)
Open issues delta
- accelerate
- Unknown
- DeepLearningExamples
- -1 (30d)
Full report
- accelerate
- Trust report
- DeepLearningExamples
- Trust report
Choose accelerate if…
- accelerate is primarily Python; DeepLearningExamples is Jupyter Notebook.
- Tags unique to accelerate: deepspeed, fsdp, mixed precision, pytorch.
- 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 DeepLearningExamples if…
- DeepLearningExamples is primarily Jupyter Notebook; accelerate is Python.
- Tags unique to DeepLearningExamples: computer-vision, deep-learning, drug-discovery, forecasting.
- The NVIDIA GPU Cloud (NGC) Container Registry that integrates with this tool offers the latest updates every month along with rigorous quality assurance.
When NOT to use DeepLearningExamples
- Avoid using DeepLearningExamples if you do not have access to NVIDIA GPUs, as it is heavily optimized for these specific hardware configurations to provide maximum utilization of Tensor Cores.
- If your project requires frameworks that are less common (e.g., MXNet or PaddlePaddle) without the same level of support as PyTorch and TensorFlow on this platform, consider other repositories that n
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 (NVIDIA/DeepLearningExamples) · observed Aug 17, 2026
- GitHub forks (NVIDIA/DeepLearningExamples) · observed Aug 17, 2026
- Last push (NVIDIA/DeepLearningExamples) · observed Aug 12, 2024
- License file (unknown) · observed Aug 17, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: accelerate 9.8k · DeepLearningExamples 15k (synced Aug 3, 2026).
Common questions
- What is the difference between accelerate and DeepLearningExamples?
- accelerate: A tool for launching, training, and using PyTorch models with ease on various devices, configurations, including mixed precision support.. DeepLearningExamples: State-of-the-Art Deep Learning scripts for various applications. See the comparison table for live GitHub stats and shared categories.
- When should I choose accelerate over DeepLearningExamples?
- Choose accelerate over DeepLearningExamples when accelerate is primarily Python; DeepLearningExamples is Jupyter Notebook; Tags unique to accelerate: deepspeed, fsdp, mixed precision, pytorch; Easy mixed-precision support for PyTorch models.
- When should I choose DeepLearningExamples over accelerate?
- Choose DeepLearningExamples over accelerate when DeepLearningExamples is primarily Jupyter Notebook; accelerate is Python; Tags unique to DeepLearningExamples: computer-vision, deep-learning, drug-discovery, forecasting; The NVIDIA GPU Cloud (NGC) Container Registry that integrates with this tool offers the latest updates every month along with rigorous quality assurance.
- 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 DeepLearningExamples?
- Avoid using DeepLearningExamples if you do not have access to NVIDIA GPUs, as it is heavily optimized for these specific hardware configurations to provide maximum utilization of Tensor Cores. If your project requires frameworks that are less common (e.g., MXNet or PaddlePaddle) without the same level of support as PyTorch and TensorFlow on this platform, consider other repositories that n
- Is accelerate or DeepLearningExamples more popular on GitHub?
- DeepLearningExamples has more GitHub stars (14,844 vs 9,803). Stars measure visibility, not whether either tool fits your constraints.
- Are accelerate and DeepLearningExamples open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to accelerate or DeepLearningExamples?
- GraphCanon lists graph-backed alternatives at accelerate alternatives and DeepLearningExamples alternatives (accelerate markdown twin, DeepLearningExamples 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 DeepLearningExamples?
- accelerate: Very active. DeepLearningExamples: 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 DeepLearningExamples?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: accelerate trust report; DeepLearningExamples trust report.