Instructions to use Tommert25/robbert_dataaugmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tommert25/robbert_dataaugmentation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Tommert25/robbert_dataaugmentation")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Tommert25/robbert_dataaugmentation") model = AutoModelForTokenClassification.from_pretrained("Tommert25/robbert_dataaugmentation") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f39841d9b115319d1f5a80776c1c2fda596eb353f11e64b6ddbf4aeefb86cd78
- Size of remote file:
- 4.09 kB
- SHA256:
- 49bac4c9f2cfe41436bffb20414df536a28a1ec4bbac0d90345be2f2f7374d1c
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