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:
- b7e6f16e801d7b373d52c5bfdc063cfe2e0d27c194f36374173fcaad6da378f1
- Size of remote file:
- 436 MB
- SHA256:
- 84e7ada7c449c648d6f92b8efb9f03064dd55a33b146993fb126324e6797bcb8
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