Instructions to use mbruton/gal_sp_mBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/gal_sp_mBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/gal_sp_mBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/gal_sp_mBERT") model = AutoModelForTokenClassification.from_pretrained("mbruton/gal_sp_mBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3bd5838251409d4c86eb3f9034e37217742c3fee654d5f828aa5f86c3086e7d
- Size of remote file:
- 709 MB
- SHA256:
- 0c8ff3193a40e457469f08975787d5619a0bdd0769dc365e0e902e18668d9dd2
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