Text Classification
Transformers
Safetensors
Kabyle
ber
xlm-roberta
emotion-classification
african-languages
amazigh
low-resource
goemotions
afro-asiatic
Eval Results (legacy)
text-embeddings-inference
Instructions to use boffire/kabyle-emotion-afro-xlmr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boffire/kabyle-emotion-afro-xlmr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="boffire/kabyle-emotion-afro-xlmr")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("boffire/kabyle-emotion-afro-xlmr") model = AutoModelForSequenceClassification.from_pretrained("boffire/kabyle-emotion-afro-xlmr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 22ac216b8edff31da585cbf6d1467f2f23b49580e7db2c03a14833ad2462d362
- Size of remote file:
- 16.8 MB
- SHA256:
- c0cb7277b7f6efc61e33bc5daf6f17142babb0bb68b2d5dd600c96471a90c62e
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