Feature Extraction
Transformers
PyTorch
TensorFlow
JAX
multilingual
Portuguese
bert
bert-large-portuguese-cased
semantic role labeling
finetuned
Instructions to use liaad/srl-pt_bertimbau-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use liaad/srl-pt_bertimbau-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="liaad/srl-pt_bertimbau-large")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("liaad/srl-pt_bertimbau-large") model = AutoModel.from_pretrained("liaad/srl-pt_bertimbau-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad89a6797bbaf14a4f243b5628b53c34f061926a7089ec8b91542c9de78fd7dd
- Size of remote file:
- 1.34 GB
- SHA256:
- 7eda63627675105b21dbe240156ae530509f07c02262ee511c98668f73b51601
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