Instructions to use Intel/distilbert-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/distilbert-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/distilbert-base-uncased-sparse-90-unstructured-pruneofa")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Intel/distilbert-base-uncased-sparse-90-unstructured-pruneofa") model = AutoModelForMaskedLM.from_pretrained("Intel/distilbert-base-uncased-sparse-90-unstructured-pruneofa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87bd6d4eabe1b16ec3971493bcb502390535915a129ec733f19e344a2999f223
- Size of remote file:
- 428 MB
- SHA256:
- d38159bc1ed73a215eb1c840f8750b0156bf450c84d6d5fb5a6108d676b6647b
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