Instructions to use ruanchaves/mdeberta-v3-base-hatebr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ruanchaves/mdeberta-v3-base-hatebr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ruanchaves/mdeberta-v3-base-hatebr")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ruanchaves/mdeberta-v3-base-hatebr") model = AutoModelForSequenceClassification.from_pretrained("ruanchaves/mdeberta-v3-base-hatebr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Parent(s): 058beaa
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README.md
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@@ -56,7 +56,7 @@ In the meanwhile, if you would like to cite our work or models before the public
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author = {Chaves Rodrigues, Ruan and Tanti, Marc and Agerri, Rodrigo},
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doi = {10.5281/zenodo.7781848},
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month = {3},
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title = ,
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url = {https://github.com/ruanchaves/eplm},
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version = {1.0.0},
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year = {2023}
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author = {Chaves Rodrigues, Ruan and Tanti, Marc and Agerri, Rodrigo},
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doi = {10.5281/zenodo.7781848},
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month = {3},
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title = {{Evaluation of Portuguese Language Models}},
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url = {https://github.com/ruanchaves/eplm},
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version = {1.0.0},
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year = {2023}
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