Instructions to use sosuke/ease-bert-base-multilingual-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sosuke/ease-bert-base-multilingual-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sosuke/ease-bert-base-multilingual-cased")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sosuke/ease-bert-base-multilingual-cased") model = AutoModel.from_pretrained("sosuke/ease-bert-base-multilingual-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe22263d9889e231eafc019af32a66da1abcce0ecf690fef92adcacb2cd4a21f
- Size of remote file:
- 711 MB
- SHA256:
- 89da94ae336495a5d65edb5c8f8c56236bc718c8a82a3e676c33b048a4c25377
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