Instructions to use LJD89/roberta_quote_detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LJD89/roberta_quote_detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LJD89/roberta_quote_detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LJD89/roberta_quote_detector") model = AutoModelForSequenceClassification.from_pretrained("LJD89/roberta_quote_detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- be3abd20f41d267029365788da9a01a4feaaaf869eb8c6a7ca696d738db0caa2
- Size of remote file:
- 499 MB
- SHA256:
- 7548e66abdf52fd082bcf0a76505e147e0f33221398c238c46b8a4d7bc080928
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