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:
- 0857bbb6108c9a605d632f8a4c0e1e31ff8beb8470e8e98cec21174f55442b48
- Size of remote file:
- 4.09 kB
- SHA256:
- b623955c29e9677962af9f3b076bb6978b4600d8edbfcfed628bdd19ddf0aa07
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