Text Classification
Transformers
PyTorch
Safetensors
Spanish
roberta
spanish
bertin
text-embeddings-inference
Instructions to use somosnlp-hackathon-2022/readability-es-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-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-paragraphs")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("somosnlp-hackathon-2022/readability-es-paragraphs") model = AutoModelForSequenceClassification.from_pretrained("somosnlp-hackathon-2022/readability-es-paragraphs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Readability ES: Paragraph-based model for two classes.
F1 macro score on validation set: `0.8891`.fc1019b