Instructions to use research-dump/roberta_temp_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use research-dump/roberta_temp_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="research-dump/roberta_temp_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("research-dump/roberta_temp_classifier") model = AutoModelForSequenceClassification.from_pretrained("research-dump/roberta_temp_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3a098d75bafdd9d0b5abc3b7493dd6e22f445ee9b88f34d43289085540ce092
- Size of remote file:
- 3.9 kB
- SHA256:
- 21ae5cfdfab4dae8aeefc66321b0d18bf6e1c227299b6c69f644da63eb997826
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