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:
- fe1d20f2adeb8bafc9d2418e815a8d410ede911269210e348cfd55a586d67f25
- Size of remote file:
- 253 MB
- SHA256:
- 15a9661486ed016a2ad717e37b7949d5617dca271e491359bc3ad260bb13f542
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