Instructions to use dicta-il/dictabert-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dicta-il/dictabert-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dicta-il/dictabert-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dicta-il/dictabert-ner") model = AutoModelForTokenClassification.from_pretrained("dicta-il/dictabert-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b50036b7ceb6181c51786139506f8973ba31817f30126769e74918209df82f4f
- Size of remote file:
- 735 MB
- SHA256:
- 3db6262c300a410bbbd20ffb480788a9f0f070ae49e76bbb3ca8f1e894978f6e
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