Text Classification
Transformers
Safetensors
dihya
feature-extraction
berber
amazigh
kabyle
tashelhit
tarifit
tamasheq
tamazight
shawiya
language-identification
conformal-prediction
low-resource
custom_code
Eval Results (legacy)
Instructions to use agbalu/Dihya-5M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agbalu/Dihya-5M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="agbalu/Dihya-5M", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("agbalu/Dihya-5M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,794 Bytes
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