Instructions to use Dev-DGT/food-dbert-multiling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dev-DGT/food-dbert-multiling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Dev-DGT/food-dbert-multiling")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Dev-DGT/food-dbert-multiling") model = AutoModelForTokenClassification.from_pretrained("Dev-DGT/food-dbert-multiling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Test v2
Browse files
README.md
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- text: "El paciente se alimenta de pan, sopa de calabaza y coca-cola"
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- text: "No se recomienda comer más de 5 porciones de espinaca, debiese comer más cereales integrales"
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# Token classification for FOODs.
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# Token classification for FOODs.
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