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:
- 7c77a859f0ecfa257e464e81455952513647adb17548e08748ade5c7d592b045
- Size of remote file:
- 539 MB
- SHA256:
- a0ffd449e1adf2e35127a80fc6cd667cd938985c0b9d2e62ebdb5af4be49227f
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