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:
- 6b3cc9526732827e80234e3fe78f8042c827f93fb4929e5798efd474d671b36b
- Size of remote file:
- 465 MB
- SHA256:
- 3709318452ce9c4b036b15289e2eeddbfff301af5604925c76252a3cc777874d
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