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:
- 6fee55e102cf986518f48c4d11d7529972814a00c1104dfc3fe0def760ab7519
- Size of remote file:
- 438 MB
- SHA256:
- 8d21925c4ff6d2aa42a1c52380a73c2c56f3280f6573034c0b60ef13e7c84fec
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