Instructions to use cook/cicero-similis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cook/cicero-similis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="cook/cicero-similis")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("cook/cicero-similis") model = AutoModelForMaskedLM.from_pretrained("cook/cicero-similis") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31b318805709a393ca2a90fbc148411ee4c810162a7f9d745fcbc9dfcc41e3c0
- Size of remote file:
- 251 MB
- SHA256:
- 0e6882aa3f3848125ba6bfd788f8dcbb1ee457d6f3302e05902f8caa5628f991
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