Instructions to use mohammadmahdinouri/moa-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohammadmahdinouri/moa-checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mohammadmahdinouri/moa-checkpoints")# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("mohammadmahdinouri/moa-checkpoints", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c28cde4a76d5b5318ca88f6fa4c654f67d18d381787ac70e7e99ab34503c7d8
- Size of remote file:
- 135 MB
- SHA256:
- 439028d9079492f27bc0e6ef742dd6c6a6965f201f1e8498bd25aa71b5f9558f
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