Instructions to use lukecarlate/Araci_Num_55 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lukecarlate/Araci_Num_55 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lukecarlate/Araci_Num_55")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lukecarlate/Araci_Num_55") model = AutoModelForMaskedLM.from_pretrained("lukecarlate/Araci_Num_55") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ceea97fa01e007d0d4fe64e6ed478f141c15dbd9ed3670065532fea82156a409
- Size of remote file:
- 3 kB
- SHA256:
- 26ce008c6dfd922972592b77bde6b8fd8fb030208b6e3a20d86014135bf48da4
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