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:
- 261a09aa70eeef82f39887a5cf03081de55bf4a08d59c7ce9dcf11f1eaed6db6
- Size of remote file:
- 5.3 kB
- SHA256:
- 90e2da7f7edb928e8f047cedf5fd98d4ab9ef7a8b4eb39bcd520b827f70235fd
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