Feature Extraction
Transformers
PyTorch
TensorFlow
JAX
multilingual
Portuguese
bert
bert-base-multilingual-cased
semantic role labeling
finetuned
Instructions to use liaad/srl-pt_mbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use liaad/srl-pt_mbert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="liaad/srl-pt_mbert-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("liaad/srl-pt_mbert-base") model = AutoModel.from_pretrained("liaad/srl-pt_mbert-base") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
9996c32 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:4ab93cf36efa26176d8cc804a076fbbb5c66dc64b6357e42ad842590759c47b0
size 711458388
|