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:
- 031cba11df337338ac31ec0f2332fba7ada9d29c62a411a17c9222825f5c8fd8
- Size of remote file:
- 15.3 MB
- SHA256:
- 431ec72a485a382d7e3a6063af5f54249b36e4870e0c8d079918e79cd0a4f8f1
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