Instructions to use lukecarlate/Araci_Num_11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lukecarlate/Araci_Num_11 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lukecarlate/Araci_Num_11")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lukecarlate/Araci_Num_11") model = AutoModelForMaskedLM.from_pretrained("lukecarlate/Araci_Num_11") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 70e920219ac71e3438d6712b89d7945215b105b63d5355a0b4a9d347ef9b6be3
- Size of remote file:
- 438 MB
- SHA256:
- d2bb4f744b3de5ba8f5e31b7ee0864ad4d189216a03fb6e6e9af5eef1afb7627
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