Instructions to use LoudlySoft/scibert_scivocab_uncased_squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LoudlySoft/scibert_scivocab_uncased_squad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="LoudlySoft/scibert_scivocab_uncased_squad")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("LoudlySoft/scibert_scivocab_uncased_squad") model = AutoModelForQuestionAnswering.from_pretrained("LoudlySoft/scibert_scivocab_uncased_squad") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 101feab9dd2d8ca2f1da665441be58313f4416b780bb63697a389b71861f6d2c
- Size of remote file:
- 437 MB
- SHA256:
- e4749bb4fe735c03ac1d756c404076ab439e41f6e71f4ee4ca5ca59b7f582d00
路
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