Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use robertou2/roberta-base-bne-finetuned-amazon_reviews_multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use robertou2/roberta-base-bne-finetuned-amazon_reviews_multi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="robertou2/roberta-base-bne-finetuned-amazon_reviews_multi")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("robertou2/roberta-base-bne-finetuned-amazon_reviews_multi") model = AutoModelForSequenceClassification.from_pretrained("robertou2/roberta-base-bne-finetuned-amazon_reviews_multi") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Model description
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## Intended uses & limitations
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## Model description
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Modelo de prueba del curso NLP de 0 a 100 sesion 4
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## Intended uses & limitations
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