Instructions to use distilbert/distilbert-base-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use distilbert/distilbert-base-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="distilbert/distilbert-base-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("distilbert/distilbert-base-cased") model = AutoModelForMaskedLM.from_pretrained("distilbert/distilbert-base-cased") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8d259cbb8f8a4cf77647835d6659187d81fdbb5c16228e7cb92c356eeb01e273
- Size of remote file:
- 263 MB
- SHA256:
- 89bb1c03c52a90f666a7ef6b216c5fa07608ce4355b16dc984192f1edb08b113
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