Instructions to use distilbert/distilbert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use distilbert/distilbert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="distilbert/distilbert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("distilbert/distilbert-base-uncased") model = AutoModelForMaskedLM.from_pretrained("distilbert/distilbert-base-uncased") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a6220cdc220085d6e9094ce220c8959709f63325d823a960fc675009b476b9b
- Size of remote file:
- 363 MB
- SHA256:
- e75cd1b76b546a498fe49ae3f0ca6f2ca4f2216c34010bea7232e8a0b95e93e8
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