Instructions to use Intel/bert-base-uncased-sparse-90-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-90-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-90-unstructured-pruneofa")# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("Intel/bert-base-uncased-sparse-90-unstructured-pruneofa") model = AutoModelForPreTraining.from_pretrained("Intel/bert-base-uncased-sparse-90-unstructured-pruneofa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e0b0e8183690137bcf46276ed551bf29afcd9a27a5c770f76abf4a1a3f112b39
- Size of remote file:
- 441 MB
- SHA256:
- 5e36a958e929f39ce58132dd48a322690963fe7ab7d779688c615b3faaf517ac
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