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:
- 89e5b12337fe22e2d1cb9eb6a6581f9d2f22a94222cbdbcf7cabe12e7a893df0
- Size of remote file:
- 4.22 kB
- SHA256:
- 757468d88a5a63df6b91f7ec7de9c447190c9ef3c3f5cc919e95d2bced53824c
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