Instructions to use ktrapeznikov/scibert_scivocab_uncased_squad_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ktrapeznikov/scibert_scivocab_uncased_squad_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="ktrapeznikov/scibert_scivocab_uncased_squad_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ktrapeznikov/scibert_scivocab_uncased_squad_v2") model = AutoModelForQuestionAnswering.from_pretrained("ktrapeznikov/scibert_scivocab_uncased_squad_v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 942f7c77d4f844a61e6d17c74accd963c75102028c67441daf1dac4c6649f051
- Size of remote file:
- 437 MB
- SHA256:
- d85a58b09a5eef8e4e962cb92364616963048858f3159f0233501a9a15494e47
路
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