Instructions to use hiiamsid/BETO_es_binary_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hiiamsid/BETO_es_binary_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hiiamsid/BETO_es_binary_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hiiamsid/BETO_es_binary_classification") model = AutoModelForSequenceClassification.from_pretrained("hiiamsid/BETO_es_binary_classification") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
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Here, i have finetuned BETO spanish bert model for binary classification on spanish language.
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Dataset:
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- Text Technology classification
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Metrics:
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- loss
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- accuracy
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language:
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- es
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