Instructions to use Tommert25/RobBERTBestModelOct13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tommert25/RobBERTBestModelOct13 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Tommert25/RobBERTBestModelOct13")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Tommert25/RobBERTBestModelOct13") model = AutoModelForTokenClassification.from_pretrained("Tommert25/RobBERTBestModelOct13") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 470cd8a50d48258fadaf2c700bc737cd3b1dfbf5ce05e804941967149786206b
- Size of remote file:
- 465 MB
- SHA256:
- 1b892c70b978fdf85771aa8d37d3a815bd9a9fd212ee134a19a5ecec231d4f69
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