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:
- db3be5099ce81672045063e17d3a5f9a38c6e3eeb9311cd3199d1a67467017d2
- Size of remote file:
- 2.74 kB
- SHA256:
- 0890f8a5efa1bdca596e7c726964dc8817011914a614ad6704f0500520ac917a
路
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