Instructions to use DataScientist1122/BERT_MedQuad_15052024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DataScientist1122/BERT_MedQuad_15052024 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="DataScientist1122/BERT_MedQuad_15052024")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("DataScientist1122/BERT_MedQuad_15052024") model = AutoModelForQuestionAnswering.from_pretrained("DataScientist1122/BERT_MedQuad_15052024", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b6e02debf94f5445db469f259b41662e657516d144575b2123274ab2c99f387d
- Size of remote file:
- 5.05 kB
- SHA256:
- 14489ec661bfac560290ee0980a30e04a6208b87fae636c58bd90bd39471bfdf
路
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