Instructions to use Dizex/InstaFoodDeBERTaV3small-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dizex/InstaFoodDeBERTaV3small-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Dizex/InstaFoodDeBERTaV3small-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Dizex/InstaFoodDeBERTaV3small-NER") model = AutoModelForTokenClassification.from_pretrained("Dizex/InstaFoodDeBERTaV3small-NER") - Notebooks
- Google Colab
- Kaggle
Upload DebertaV2ForTokenClassification
Browse files- config.json +1 -1
- pytorch_model.bin +1 -1
config.json
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"_name_or_path": "/Users/meg/Repos/private/trendish/models/ner/deberta-v3-small/deberta-v3-small_531hfo2t/checkpoint-1500",
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"architectures": [
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pytorch_model.bin
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size 564962735
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