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:
- 3d862e0176d9cee60b9fa5d1f71c8929a0b855a010fe7a9ea05b865c4afc9a3c
- Size of remote file:
- 3 kB
- SHA256:
- e85caf13da118be88772f03f1b47388da37ef47e4989c503dac177990129b449
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