Text Classification
Transformers
Safetensors
Laya
Arabic
modernbert
feature-extraction
arabic
nlu
intent-classification
natural-language-inference
custom_code
Eval Results (legacy)
Instructions to use Wouze/laya-ara with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wouze/laya-ara with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Wouze/laya-ara", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Wouze/laya-ara", trust_remote_code=True) model = AutoModel.from_pretrained("Wouze/laya-ara", trust_remote_code=True, device_map="auto") - Laya
How to use Wouze/laya-ara with Laya:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Commit History
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