Instructions to use Intel/distilbert-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/distilbert-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/distilbert-base-uncased-sparse-85-unstructured-pruneofa")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Intel/distilbert-base-uncased-sparse-85-unstructured-pruneofa") model = AutoModelForMaskedLM.from_pretrained("Intel/distilbert-base-uncased-sparse-85-unstructured-pruneofa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c757046098d3e8fbe8c44e2b9f08f68d536b7b621c9a6078ac92ec859cabb35a
- Size of remote file:
- 268 MB
- SHA256:
- f71c3b3d9ab39d4138fd0a9a9db17c7cd2b248c0aa94ffccc9d8594149c8e712
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