Text Classification
Transformers
PyTorch
Spanish
roberta
emotion-recognition
speech-emotion-recognition
spanish
affective-computing
umuteam
Eval Results (legacy)
text-embeddings-inference
Instructions to use UMUTeam/MarIA-emotion-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UMUTeam/MarIA-emotion-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="UMUTeam/MarIA-emotion-es")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("UMUTeam/MarIA-emotion-es") model = AutoModelForSequenceClassification.from_pretrained("UMUTeam/MarIA-emotion-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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issn = {0920-5489},
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doi = {https://doi.org/10.1016/j.csi.2024.103856},
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url = {https://www.sciencedirect.com/science/article/pii/S0920548924000254},
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author = {Ronghao Pan and José Antonio García-Díaz and Miguel Ángel Rodríguez-García and
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```
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issn = {0920-5489},
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doi = {https://doi.org/10.1016/j.csi.2024.103856},
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url = {https://www.sciencedirect.com/science/article/pii/S0920548924000254},
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author = {Ronghao Pan and José Antonio García-Díaz and Miguel Ángel Rodríguez-García and Rafael Valencia-García},
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}
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```
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