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:
- 8de22938f83b272da1fe70eb8949f7a8117253d2a982a7aec316233bf2f4752b
- Size of remote file:
- 487 MB
- SHA256:
- db374c660ff95fab093b58d30f742a560f9d64cd3726624c83bc756328d2bac3
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