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Project comparison
Xgboost vs transformers
Compare adoption, momentum, maintenance health, and project basics before choosing which tool to evaluate deeper.
Xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
Best matched with other framework tools.
28.6K
Stars
+227
Weekly
59/100
Health
transformers
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Best matched with other framework tools.
162.8K
Stars
+220
Weekly
91/100
Health
Quick Take
Adoption
transformers has the larger GitHub footprint with 162.8K stars.
Momentum
Xgboost is currently growing faster at +227 stars this week.
Maintenance
transformers has the stronger automated maintenance signal at 91/100. This is not a security or fit verdict.
Side-by-side evidence
Use these signals to narrow your choice, then confirm setup, license, and fit upstream.
| Signal | Xgboost | transformers |
|---|---|---|
| Evidence status | Basic listing· 2d ago | Recently verified· 2d ago |
| GitHub stars | 28.6K | 162.8K |
| Weekly growth | +227 | +220 |
| Health score | Watch59/100 |
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