Instructions to use JAlexis/bert_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JAlexis/bert_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="JAlexis/bert_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("JAlexis/bert_v2") model = AutoModelForQuestionAnswering.from_pretrained("JAlexis/bert_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b05fb2123dcbda7a146921f6749a03307a0cdcf3436d18324712dcbabf0332f
- Size of remote file:
- 431 MB
- SHA256:
- 3d1ce956f357d5b2461c60ed4d27577b0ac2fdfa647af3117c1116ce9fd39061
路
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