Instructions to use globis-university/deberta-v3-japanese-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use globis-university/deberta-v3-japanese-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="globis-university/deberta-v3-japanese-base")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("globis-university/deberta-v3-japanese-base") model = AutoModelForTokenClassification.from_pretrained("globis-university/deberta-v3-japanese-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8afae71655124fcb3e05d5502ef93da86f2950fc35fdd7bf02cfbe8aa6bac29e
- Size of remote file:
- 692 kB
- SHA256:
- dcf3a8e29a7d5560b05de755b56d62d0a4e8614339d28753c664baa0e3ba7b67
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