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:
- 105cb77eba5036ce98f9a2a9958330973163292ad5e93039197577a6466ea5dd
- Size of remote file:
- 536 MB
- SHA256:
- f5d2c7eb7c62da36dd6571f7f4cec8a681431e0b671d92664418f4d4e0fc2200
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