Instructions to use 96harsh56/bert_test1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 96harsh56/bert_test1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="96harsh56/bert_test1")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("96harsh56/bert_test1") model = AutoModelForQuestionAnswering.from_pretrained("96harsh56/bert_test1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 25e1c26d70b8ef6d27282c9327e142462ab0c3eaa9c6306a6833cfc8f7f5945b
- Size of remote file:
- 436 MB
- SHA256:
- 77b768049e4a576183bd31c9b86d03f712e6e69620b1f235237e8f6a9cdde93b
路
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