Instructions to use JAlexis/bertFast_02 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JAlexis/bertFast_02 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="JAlexis/bertFast_02")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("JAlexis/bertFast_02") model = AutoModelForQuestionAnswering.from_pretrained("JAlexis/bertFast_02", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f37c2558ed8edbde9cf6a5facce01e1db7e0e382d1972e71acb5e0df22c1b878
- Size of remote file:
- 431 MB
- SHA256:
- c34660ef8a180ff331498480bede5b324200c8361c66c88ebf152c76ff4d2d90
路
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