Instructions to use chiranthans23/bert-base-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chiranthans23/bert-base-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="chiranthans23/bert-base-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("chiranthans23/bert-base-cased") model = AutoModelForQuestionAnswering.from_pretrained("chiranthans23/bert-base-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ab9f918fab72906f795241535e2d22ad551faaeb1e0763bd450827d17c6d3084
- Size of remote file:
- 431 MB
- SHA256:
- 32cb8d5361f60665ea2a7f2f9125ffa38b61e7d8cec130ea6b523e891d68cb75
路
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