Instructions to use Intel/bert-base-uncased-squadv1.1-sparse-80-1x4-block-pruneofa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/bert-base-uncased-squadv1.1-sparse-80-1x4-block-pruneofa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Intel/bert-base-uncased-squadv1.1-sparse-80-1x4-block-pruneofa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Intel/bert-base-uncased-squadv1.1-sparse-80-1x4-block-pruneofa") model = AutoModelForQuestionAnswering.from_pretrained("Intel/bert-base-uncased-squadv1.1-sparse-80-1x4-block-pruneofa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa94f9a624639501596bbee3f85ff8a84f1554657a7d01c9d41d0c0976f52fb3
- Size of remote file:
- 436 MB
- SHA256:
- 3fbeeb741116fc5499a6a6aded7b53031ef2bb440ef16f05b590adf11cd8f058
路
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