Instructions to use franklu/pubmed_bert_squadv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use franklu/pubmed_bert_squadv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="franklu/pubmed_bert_squadv2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("franklu/pubmed_bert_squadv2") model = AutoModelForQuestionAnswering.from_pretrained("franklu/pubmed_bert_squadv2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 848135023cf0a6d3c57efd48225ffa88b1858dde7db0b182082d7e2293c852a6
- Size of remote file:
- 436 MB
- SHA256:
- e9c1460c0931f526f21e2de80164d2a7fc741d58f01af7ed4f6ea0e828ac09bd
路
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