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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 796fe6b02a296f0a1315563b47bda8e0d9729c5209133594bad4c39e13394f3e
- Size of remote file:
- 465 MB
- SHA256:
- 96f721e7bd193d53c58f1ce1a86df5f3a8a56c9f7869eeb62571c0e84b672f4f
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