Instructions to use ipipan/kashubian-herbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ipipan/kashubian-herbert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ipipan/kashubian-herbert-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ipipan/kashubian-herbert-base") model = AutoModelForMaskedLM.from_pretrained("ipipan/kashubian-herbert-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea667cea6c729b0835881fab6f55a32982d8c19d57788e2c7fcfc0fb9efe9518
- Size of remote file:
- 369 MB
- SHA256:
- 440fbe063c3cf3fa8a13c43ce991db5304a532d7f5596af45ce008f17e902795
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