Instructions to use lukecarlate/Araci_Num_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lukecarlate/Araci_Num_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lukecarlate/Araci_Num_3")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lukecarlate/Araci_Num_3") model = AutoModelForMaskedLM.from_pretrained("lukecarlate/Araci_Num_3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e874235d298e8b8bc508d391f7cd2082313026957b018ba6e96242a427917297
- Size of remote file:
- 3.07 kB
- SHA256:
- 52d98ee1c7ce3f93209f21e73203e047b49b6f4da11850fcf8326242120f70bc
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