Instructions to use medkit/DrBert-Generalized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use medkit/DrBert-Generalized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="medkit/DrBert-Generalized")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("medkit/DrBert-Generalized") model = AutoModelForTokenClassification.from_pretrained("medkit/DrBert-Generalized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 739be9de46222c1dca39bf38a639704524e716ef46e1ab628d1f63b81627a88a
- Size of remote file:
- 871 MB
- SHA256:
- 12ddf17adc19b1e6347170dc0f4657d659b6ac3bf2054fbb1f3f4ea32a1e0c00
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