Instructions to use fastyBOOM/nerbert-recipe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fastyBOOM/nerbert-recipe with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="fastyBOOM/nerbert-recipe")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("fastyBOOM/nerbert-recipe") model = AutoModelForTokenClassification.from_pretrained("fastyBOOM/nerbert-recipe", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from fastyBOOM/nerbert-recipe: direct link, hf CLI and curl.
- Browser
- Download file 103 kB
-
https://huggingface.co/fastyBOOM/nerbert-recipe/resolve/main/tokenizer.json
- Command line
-
hf download hf://fastyBOOM/nerbert-recipe/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/fastyBOOM/nerbert-recipe/resolve/main/tokenizer.json
103 kB
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