Instructions to use mbruton/spa_pt_mBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/spa_pt_mBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/spa_pt_mBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/spa_pt_mBERT") model = AutoModelForTokenClassification.from_pretrained("mbruton/spa_pt_mBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb2724d1874ae77a633ee4bde3d5b7047af53d1d3e09f365400b84ecc432e3e9
- Size of remote file:
- 710 MB
- SHA256:
- bef47c64a5b96cb51055aec1cdfeef6192de25f89de8850e98121f1699a3cd53
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