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")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("UMUTeam/MarIA-emotion-es") model = AutoModelForSequenceClassification.from_pretrained("UMUTeam/MarIA-emotion-es") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- acca280d97f1ef5d6210c9eab366d9e8c295430daf87ec7f445a1c8f53e9e2f7
- Size of remote file:
- 499 MB
- SHA256:
- d9ca577f501be58b5c9f1be494bec8fd6f2d32fe8f24c1f6bf88f55daf1cafb1
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