Instructions to use Chakita/Kalbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Chakita/Kalbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Chakita/Kalbert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Chakita/Kalbert") model = AutoModelForMaskedLM.from_pretrained("Chakita/Kalbert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a36970e5af26854a82721bafd4e1fb3090f03b61cae5615cc6bf19bf9501c7b5
- Size of remote file:
- 3.39 kB
- SHA256:
- f89565f6ffae6826b7a336dfee842a36942695cb3910e6a8f841b9676b7562ec
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