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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61c6a7799a7504a88fd299b656240efe42eab2a5d00a386465297552992e3918
- Size of remote file:
- 4.03 kB
- SHA256:
- 92efae68bce5eff733b3f80eb9ce236c59dc9b7e27c4613db4ce513f8bf19df0
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