Instructions to use Naveen-k/KanBERTo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Naveen-k/KanBERTo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Naveen-k/KanBERTo")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Naveen-k/KanBERTo") model = AutoModelForMaskedLM.from_pretrained("Naveen-k/KanBERTo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f652db6fd52f7f138750506200cee01e10be507f5493917f8dc4efef3c78ad7
- Size of remote file:
- 334 MB
- SHA256:
- 48f9263d6bb8f0979eab3c81748198ef03e41f74df46b03b99dc4c8b04aecab0
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