Instructions to use lmvasque/readability-es-benchmark-bertin-es-paragraphs-2class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lmvasque/readability-es-benchmark-bertin-es-paragraphs-2class with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lmvasque/readability-es-benchmark-bertin-es-paragraphs-2class")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lmvasque/readability-es-benchmark-bertin-es-paragraphs-2class") model = AutoModelForSequenceClassification.from_pretrained("lmvasque/readability-es-benchmark-bertin-es-paragraphs-2class", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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