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:
- 649885090585a993c231cab39deee8fd9cfb215d6961d8705fd1a7a418945b9c
- Size of remote file:
- 465 MB
- SHA256:
- b85b5dcc7ecf21e090daa15f08a87d4ea9426aa0d88e77d3e8cff81c8d767055
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