Zero-Shot Classification
Transformers
Safetensors
Arabic
bert
feature-extraction
arabic
prompt-routing
router
encoder
tiny-model
Instructions to use oddadmix/Nawah-Router-BERT-6M-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oddadmix/Nawah-Router-BERT-6M-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="oddadmix/Nawah-Router-BERT-6M-v2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("oddadmix/Nawah-Router-BERT-6M-v2") model = AutoModel.from_pretrained("oddadmix/Nawah-Router-BERT-6M-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3229c8ac12617e9939eb9d2814dc47e2cf46662ad153b0ae706446524fc96b9b
- Size of remote file:
- 23.9 MB
- SHA256:
- c4ac75d8967e7b5f132c74564e7e3421be08b73a0447695adb1ef5a5feff1482
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