Instructions to use Shresthadev403/ner-bert-ingredients with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shresthadev403/ner-bert-ingredients with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Shresthadev403/ner-bert-ingredients")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Shresthadev403/ner-bert-ingredients") model = AutoModelForTokenClassification.from_pretrained("Shresthadev403/ner-bert-ingredients", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Shresthadev403/ner-bert-ingredients: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
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https://huggingface.co/Shresthadev403/ner-bert-ingredients/resolve/main/tokenizer.json
- Command line
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hf download hf://Shresthadev403/ner-bert-ingredients/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Shresthadev403/ner-bert-ingredients/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.