Instructions to use medspaner/xlm-roberta-large-spanish-trials-cases-medic-attr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use medspaner/xlm-roberta-large-spanish-trials-cases-medic-attr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="medspaner/xlm-roberta-large-spanish-trials-cases-medic-attr")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("medspaner/xlm-roberta-large-spanish-trials-cases-medic-attr") model = AutoModelForTokenClassification.from_pretrained("medspaner/xlm-roberta-large-spanish-trials-cases-medic-attr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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widget:
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- text: Azitromicina en suspensión oral, 10 mg/kg una vez al día durante siete días
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- text: A un grupo se le administró Ciprofloxacino 200 mg bid EV y al otro Cefazolina 1 g tid IV
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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