Zero-Shot Classification
Transformers
Safetensors
Arabic
llama
feature-extraction
arabic
prompt-routing
router
text-generation-inference
Instructions to use oddadmix/Nawah-Router-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oddadmix/Nawah-Router-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="oddadmix/Nawah-Router-v3")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("oddadmix/Nawah-Router-v3") model = AutoModel.from_pretrained("oddadmix/Nawah-Router-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 48a98f17cd8e6871db3c7c6978efb5357e9953c0c55b69cfef6a028fd56c48a1
- Size of remote file:
- 207 MB
- SHA256:
- b5200d894303508b35530632e7f86e433596cb9dd9a0e6eb124aaf20a75b8f8c
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