Instructions to use marquesafonso/bertimbau-large-ner-total with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marquesafonso/bertimbau-large-ner-total with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="marquesafonso/bertimbau-large-ner-total")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("marquesafonso/bertimbau-large-ner-total") model = AutoModelForTokenClassification.from_pretrained("marquesafonso/bertimbau-large-ner-total") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- db03549f49361e6d782963022c223977bedff25ab2a19437fea255e241fee6ff
- Size of remote file:
- 436 MB
- SHA256:
- c8702e36f7377b71dcdc5571f1f52f0c64f228a014eca08a482b386c3c89130c
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