Instructions to use Farnazgh/distilbert_squadv2_answerable_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Farnazgh/distilbert_squadv2_answerable_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Farnazgh/distilbert_squadv2_answerable_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Farnazgh/distilbert_squadv2_answerable_classifier") model = AutoModelForSequenceClassification.from_pretrained("Farnazgh/distilbert_squadv2_answerable_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 18646be476d289c20a652b9049b2a8ce2205590e9a351214b22ba07bab228969
- Size of remote file:
- 268 MB
- SHA256:
- 2a9b0bb214dee1f22a9bbae8ec375c7655943c398d82cbed1744eedab6f6c6d0
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