Instructions to use ixa-ehu/SciBERT-SQuAD-QuAC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ixa-ehu/SciBERT-SQuAD-QuAC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="ixa-ehu/SciBERT-SQuAD-QuAC")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ixa-ehu/SciBERT-SQuAD-QuAC") model = AutoModelForQuestionAnswering.from_pretrained("ixa-ehu/SciBERT-SQuAD-QuAC") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4284fb2119325dcf3411f4499edc3bd6cf27fc43db1a51d0175c551e8eb1c813
- Size of remote file:
- 440 MB
- SHA256:
- 865781d9dad87cc2822b17e845109d10c428bf20e1d19938269d0f0d0e972004
路
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