Instructions to use uw-madison/mra-base-512-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uw-madison/mra-base-512-4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="uw-madison/mra-base-512-4")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("uw-madison/mra-base-512-4") model = AutoModelForMaskedLM.from_pretrained("uw-madison/mra-base-512-4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57f1d3f23327733423fd5a941c4861f9430e8fd7c6b0cf71c2d4f6cdec839e5c
- Size of remote file:
- 499 MB
- SHA256:
- e5de1e48b7c21afe66a9abfb4cddcf24ae387ae3ab3ecf20de3a259506e80bf0
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