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:
- 8562017b133e0914a9758af196520ff5306b44cd75d6af53e9559e8a9b08feb7
- Size of remote file:
- 3.45 kB
- SHA256:
- 2771247c7460111fd9246e68396e46eb6ddd37ebf0a6a76c0da612daee7d5971
路
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