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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a184b2b11046834b0cd331a6add8c60f316cd5fc20f545baf507182cfc22a21
- Size of remote file:
- 17.1 MB
- SHA256:
- 3a56def25aa40facc030ea8b0b87f3688e4b3c39eb8b45d5702b3a1300fe2a20
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