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")# 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
- Xet hash:
- d125e7375db856750cb30c38d23c0cb50f3efa72735f08abad5d0e2efbb19a6f
- Size of remote file:
- 2.22 kB
- SHA256:
- 239c758b2360415a1c062fa852e630b1afa292dea48eccff45ce37b95bbf0ca5
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