Instructions to use research-dump/roberta_temp_classifier_bootstrapped with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use research-dump/roberta_temp_classifier_bootstrapped with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="research-dump/roberta_temp_classifier_bootstrapped")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("research-dump/roberta_temp_classifier_bootstrapped") model = AutoModelForSequenceClassification.from_pretrained("research-dump/roberta_temp_classifier_bootstrapped") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f30fe6abb5b0d28baaf574e30a8d69b0f490bce40d442bbd7aa92c72634724b9
- Size of remote file:
- 499 MB
- SHA256:
- 9e0d048c46da40176cb0dbf0cfe71b47aa13a90fd6a5cb185f59b04728f956f0
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