Instructions to use Tommert25/MultiBERTBestModelOct13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tommert25/MultiBERTBestModelOct13 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Tommert25/MultiBERTBestModelOct13")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Tommert25/MultiBERTBestModelOct13") model = AutoModelForTokenClassification.from_pretrained("Tommert25/MultiBERTBestModelOct13", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f2300b012fdb8eaac9e6e254ab5c8792f1a59eac18908d90c6da274071167ed4
- Size of remote file:
- 667 MB
- SHA256:
- 1d7f806697f712dfe073c320cce2914261c8ad38e567a6fa5dda5c8cc5406424
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