Instructions to use Cabooose/token_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cabooose/token_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Cabooose/token_classification_model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Cabooose/token_classification_model") model = AutoModelForTokenClassification.from_pretrained("Cabooose/token_classification_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f355c089c1d61eeacdd531c5ff5f57bb50784cff3ae3832ee17d0e9b37c4dd1
- Size of remote file:
- 431 MB
- SHA256:
- 4a8125c1ac92d4ea3f8777933de783f02080e4b7b588ea297d3554f4b371f722
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