Instructions to use iknlpt3/regression_xlm_roberta_divemt_ita with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iknlpt3/regression_xlm_roberta_divemt_ita with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="iknlpt3/regression_xlm_roberta_divemt_ita")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("iknlpt3/regression_xlm_roberta_divemt_ita") model = AutoModelForSequenceClassification.from_pretrained("iknlpt3/regression_xlm_roberta_divemt_ita") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 786845bb337343392e00286e63cd1bf0d574a7f43623ac444255438e0435520b
- Size of remote file:
- 1.11 GB
- SHA256:
- 8f5d755c8afb685716274af87c123a116c11f5eca7598734f3ce6e568ae7bb7a
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