Instructions to use mudes/multilingual-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mudes/multilingual-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mudes/multilingual-base")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mudes/multilingual-base") model = AutoModelForTokenClassification.from_pretrained("mudes/multilingual-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a760508b9130a041b7735f37a31469c506cae1770ca1066b829fad29578e706
- Size of remote file:
- 2.42 kB
- SHA256:
- f174797438ca2ffffa991207b5c01090e43ad06e0e3d24ea25234906f615d273
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