Instructions to use JackBAI/crate-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JackBAI/crate-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="JackBAI/crate-base")# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("JackBAI/crate-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78a71b343b1f798f5d021964d522d9870d08d9e701091d99eeddde68f9a4e3b4
- Size of remote file:
- 244 MB
- SHA256:
- ad05443bb4992738036eb12e9ac0a5d45dd0401326160a09f1359826b8c4889f
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