Instructions to use marcostrfn/bart-base-spanish-nli-taller-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcostrfn/bart-base-spanish-nli-taller-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcostrfn/bart-base-spanish-nli-taller-test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcostrfn/bart-base-spanish-nli-taller-test") model = AutoModelForSequenceClassification.from_pretrained("marcostrfn/bart-base-spanish-nli-taller-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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- bart
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library_name: transformers
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pipeline_tag: zero-shot-classification
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widget:
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- text: "El Real Madrid ha ganado la Champions League."
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candidate_labels: "deportes, política, economía, ciencia"
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example_title: "Ejemplo Zero-Shot"
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---
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# BART for Natural Language Inference (MNLI Custom)
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- bart
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library_name: transformers
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pipeline_tag: zero-shot-classification
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base_model: facebook/bart-base
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datasets:
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widget:
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- text: "El Real Madrid ha ganado la Champions League."
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candidate_labels: "deportes, política, economía, ciencia"
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example_title: "Ejemplo Zero-Shot"
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inference:
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parameters:
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hypothesis_template: "Este ejemplo trata sobre {}."
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---
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# BART for Natural Language Inference (MNLI Custom)
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