Instructions to use lukecarlate/Araci_Num_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lukecarlate/Araci_Num_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lukecarlate/Araci_Num_3")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lukecarlate/Araci_Num_3") model = AutoModelForMaskedLM.from_pretrained("lukecarlate/Araci_Num_3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1d7acbcbe729a39453691420c78ecc0b16536956d67f0d03269d052c7903f1b
- Size of remote file:
- 438 MB
- SHA256:
- 33dce6b94a58fb67a5d40ba3f1c9f4179493e73fc9e10faeb35b2871ed3421e5
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