Instructions to use lukecarlate/Araci_Num_88 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lukecarlate/Araci_Num_88 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lukecarlate/Araci_Num_88")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lukecarlate/Araci_Num_88") model = AutoModelForMaskedLM.from_pretrained("lukecarlate/Araci_Num_88") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f62fba4f7406c588fc32298f436f0be5c6b70d7b49e004f5854305f67443f4c
- Size of remote file:
- 438 MB
- SHA256:
- 744b3f7db7357d4356450207233588b8781b8fbe7b2618d1952067bcc1f7457e
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