transformers_circleci_workflow_runs
CircleCI workflow run records for the Transformers library.
Open dataset Updated 2026-06-16
What is transformers_circleci_workflow_runs?
The transformers_circleci_workflow_runs dataset consists of data from CircleCI workflow executions related to the Transformers library.
It supports analysis of continuous integration processes within AI and machine learning development workflows.
What you can build with transformers_circleci_workflow_runs
Track CI build trends
Plot success rates and durations of transformers CI runs over time to spot regressions in the library's test suite.
Detect flaky tests
Filter workflow records to find jobs that intermittently fail and correlate them with specific code changes or dependencies.
Benchmark workflow efficiency
Compare run times across different CircleCI configurations to evaluate optimizations for large Hugging Face repositories.
Load transformers_circleci_workflow_runs
Python
from datasets import load_dataset
ds = load_dataset("hf-internal-testing/transformers_circleci_workflow_runs")- 1Install the datasets library with pip install datasets
- 2Import load_dataset from the datasets package
- 3Call load_dataset('hf-internal-testing/transformers_circleci_workflow_runs')
- 4Inspect the returned DatasetDict for available splits and column names
- 5Query or filter rows to analyze specific workflow fields
transformers_circleci_workflow_runs: pros & cons
Pros
- +Real production CI data from the widely used transformers repo
- +Directly loadable with the standard Hugging Face datasets API
- +Focused on infrastructure metrics useful for MLOps analysis
- +Maintained under the hf-internal-testing organization
Cons
- –No dataset size or schema details are published
- –Restricted to CircleCI runs of a single repository
- –No task tags or documentation on column meanings provided
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Frequently asked questions
A collection of CircleCI workflow run records from the Hugging Face transformers repository.
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