Instructions to use mohammadmahdinouri/moa-vanilla-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohammadmahdinouri/moa-vanilla-checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mohammadmahdinouri/moa-vanilla-checkpoints")# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("mohammadmahdinouri/moa-vanilla-checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 525df7b6364048aa5a5e869e9ef5eac1df99a519afa365aac0a5cfcf971c6dff
- Size of remote file:
- 114 MB
- SHA256:
- c30a9d4691f0d5c5112e4de59e3a98a5ef9023f2ccc0568fe07b1bf6a059e730
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