Instructions to use arver/distilbert_squad2_custom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arver/distilbert_squad2_custom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="arver/distilbert_squad2_custom")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("arver/distilbert_squad2_custom") model = AutoModelForQuestionAnswering.from_pretrained("arver/distilbert_squad2_custom") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c12ccee728ade097ead33bbff64a659da3c86961d93fc5b52dc1f45c416f5542
- Size of remote file:
- 1.45 kB
- SHA256:
- 0a03aa6fece54ff48734e95565bf1eb9285a1bd8a67c63065d83abaaccb44b2d
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