Text Classification
Transformers
TensorFlow
roberta
generated_from_keras_callback
text-embeddings-inference
Instructions to use nathanReitinger/mlcb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nathanReitinger/mlcb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nathanReitinger/mlcb")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nathanReitinger/mlcb") model = AutoModelForSequenceClassification.from_pretrained("nathanReitinger/mlcb") - Notebooks
- Google Colab
- Kaggle
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# Citation
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@inproceedings{reitinger2021ml,
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title={ML-CB: Machine Learning Canvas Block.},
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author={Nathan Reitinger and Michelle L Mazurek},
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pages={453--473},
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year={2021}
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}
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- [OSF]
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- [GitHub]
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- [Data]
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# Citation
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```
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@inproceedings{reitinger2021ml,
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title={ML-CB: Machine Learning Canvas Block.},
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author={Nathan Reitinger and Michelle L Mazurek},
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pages={453--473},
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year={2021}
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}
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```
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- [OSF](https://osf.io/shbe7/)
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- [GitHub](https://github.com/SP2-MC2/ML-CB)
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- [Data](https://dataverse.harvard.edu/dataverse/ml-cb)
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