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:
- 2de7265cfec3f8093fe4b2b0eda19e43a32c3eaa3f74ed477030f91df6a3eb80
- Size of remote file:
- 1.42 GB
- SHA256:
- 12deef369dae53cfdade26635e773b7382dd6ca65fc670693dd0d31b8d81b10c
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