Instructions to use emanjavacas/MacBERTh-ing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emanjavacas/MacBERTh-ing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="emanjavacas/MacBERTh-ing")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("emanjavacas/MacBERTh-ing") model = AutoModelForSequenceClassification.from_pretrained("emanjavacas/MacBERTh-ing") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
Sequence Classification model fine-tuned from emanjavacas/MacBERTh on a dataset of manually annotated ing-forms.
The classification schemes is as follows:
['NAME', 'NOMINAL-ING', 'NOUN', 'PARTICIPLE', 'VERB']
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