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:
- 22c01c6ef7f5533858aefbd82394ef70da80cf492d9ce7d2a97cea2f242afc07
- Size of remote file:
- 465 MB
- SHA256:
- 753a0056b6794eddebfcf945f4399adbf2ea909e0a1d1369bd8352416d8f99af
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