Instructions to use redsat/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use redsat/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="redsat/model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("redsat/model") model = AutoModelForMaskedLM.from_pretrained("redsat/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c934248fc4657fa37ae5a13f2ae95fe3d31491bbe34f2b5108f3b83c7779c667
- Size of remote file:
- 2.24 GB
- SHA256:
- c90fe26fd285a5881e806e6b4626cf982897354f8453b972e43f5ff44cc37c06
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