Instructions to use Intel/bert-base-uncased-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-sparse-80-1x4-block-pruneofa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Intel/bert-base-uncased-sparse-80-1x4-block-pruneofa")# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("Intel/bert-base-uncased-sparse-80-1x4-block-pruneofa") model = AutoModelForPreTraining.from_pretrained("Intel/bert-base-uncased-sparse-80-1x4-block-pruneofa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b28094005b2ba443c07c8e81a6df3b5aba4736ef887379f1a65d9c6c7927f9e
- Size of remote file:
- 582 MB
- SHA256:
- d7b7d61ea728f3041d0816072af827a9fb03ba8eabf31c0a511985d660dc38e9
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