Instructions to use hung200504/bert-25 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hung200504/bert-25 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hung200504/bert-25")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hung200504/bert-25") model = AutoModelForQuestionAnswering.from_pretrained("hung200504/bert-25") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6100653dc7459ef3cc25ce8684e55245349450555bb67412baaf001e3bd1c5ad
- Size of remote file:
- 431 MB
- SHA256:
- 86b0d3da79342c1b1c3707f2a832f2a9dc9011fe9ee2e823fb45dc1640574c27
路
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