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:
- 917329ceede3f8abcc80083f961fc1268ada318a25648d7b0b49620bf006ada8
- Size of remote file:
- 3 kB
- SHA256:
- 0043535f7f387597b77774fa5454d2505154ede268debb12e3cf18e4bcfa2397
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