Text Classification
Transformers
PyTorch
Safetensors
Spanish
roberta
spanish
bertin
text-embeddings-inference
Instructions to use somosnlp-hackathon-2022/readability-es-3class-paragraphs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use somosnlp-hackathon-2022/readability-es-3class-paragraphs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="somosnlp-hackathon-2022/readability-es-3class-paragraphs")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("somosnlp-hackathon-2022/readability-es-3class-paragraphs") model = AutoModelForSequenceClassification.from_pretrained("somosnlp-hackathon-2022/readability-es-3class-paragraphs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cfe24c19c98086280fd1964e8a251d4231e1b1f703790028fa7a1a8a81c005fe
- Size of remote file:
- 499 MB
- SHA256:
- bb1750a7b93269c6ec7f975b2e751c8b99205c09a8ab3d13794d3df69c9eb27e
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