Instructions to use dsfsi/PuoBERTaJW300 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dsfsi/PuoBERTaJW300 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dsfsi/PuoBERTaJW300")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dsfsi/PuoBERTaJW300") model = AutoModelForMaskedLM.from_pretrained("dsfsi/PuoBERTaJW300") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39143edc8d2c70797654447a3d32084d2ca4e2140aef924350e8029c7b0c62b5
- Size of remote file:
- 334 MB
- SHA256:
- 3f1ab761d7f88e31c5da9773b53be0fc3ac85c207c6b251903bdf737b1d521b9
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