Instructions to use dvb555/distilbert-answer-scoring-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dvb555/distilbert-answer-scoring-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dvb555/distilbert-answer-scoring-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dvb555/distilbert-answer-scoring-classification") model = AutoModelForSequenceClassification.from_pretrained("dvb555/distilbert-answer-scoring-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 135529e4407a072feab2d7815de1035d6299ab284d709edd00bdb8974e0fc15c
- Size of remote file:
- 268 MB
- SHA256:
- cac977a4b2d951b8b19960dad0cfbf07b45362ed1f49b625dd57abbc52a91398
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