Instructions to use Intel/bert-base-uncased-sparse-85-unstructured-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-85-unstructured-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-85-unstructured-pruneofa")# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("Intel/bert-base-uncased-sparse-85-unstructured-pruneofa") model = AutoModelForPreTraining.from_pretrained("Intel/bert-base-uncased-sparse-85-unstructured-pruneofa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5e27ad56a286759ff0bfe00a75ca6ce74357c49254027c809a8337ed8cd18153
- Size of remote file:
- 441 MB
- SHA256:
- ef450f8634175465652a4e8de724063727a5b93c8fa2dd3171b4a5385265494b
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