Instructions to use mbruton/gal_ptsp_XLM-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/gal_ptsp_XLM-R with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/gal_ptsp_XLM-R")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/gal_ptsp_XLM-R") model = AutoModelForTokenClassification.from_pretrained("mbruton/gal_ptsp_XLM-R") - Notebooks
- Google Colab
- Kaggle
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README.md
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### Training Data
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This model was pre-trained on the [PropBank.Br Portuguese SRL corpus](http://www.nilc.icmc.usp.br/portlex/index.php/en/projects/propbankbringl) and the [SpanishSRL Dataset](
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This model was fine-tuned on the "train" portion of the [GalicianSRL Dataset](https://huggingface.co/datasets/mbruton/galician_srl) produced as part of this same project.
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#### Training Hyperparameters
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### Training Data
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This model was pre-trained on the [PropBank.Br Portuguese SRL corpus](http://www.nilc.icmc.usp.br/portlex/index.php/en/projects/propbankbringl) and the [SpanishSRL Dataset](https://huggingface.co/datasets/mbruton/spanish_srl) produced as part of this same project.
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This model was fine-tuned on the "train" portion of the [GalicianSRL Dataset](https://huggingface.co/datasets/mbruton/galician_srl) produced as part of this same project.
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#### Training Hyperparameters
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