Instructions to use arodriguezf/mmbert-multi-borrowings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arodriguezf/mmbert-multi-borrowings with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="arodriguezf/mmbert-multi-borrowings")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("arodriguezf/mmbert-multi-borrowings") model = AutoModelForTokenClassification.from_pretrained("arodriguezf/mmbert-multi-borrowings", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3fc6dd166dec97ff8ce03e69dff16acc288367f1613bf3aa99f4f1f6f11283ef
- Size of remote file:
- 34.4 MB
- SHA256:
- c00217a639d38b476f04dd77e6e25eb90dbed0ad2a55a9a882534221267fcf83
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