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:
- 2a33856e425784798d9b68b251a3e6f6b7824973f03ea2019ae793bba7ccb9ea
- Size of remote file:
- 2.86 kB
- SHA256:
- 506b55a37c981199d68006c6ab85d5db9ac88f9af852bea5bacc2fef04084d99
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