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:
- 56e604a80296d812900b2891a4ecd0e657b611430efcf071a387ecf6cc37099d
- Size of remote file:
- 333 kB
- SHA256:
- fee73bafca13591d81459fffbdb715ce01222337f8080e49ce44f5b80415029f
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