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")# pip install -U transformers accelerate # 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
Download tokenizer.json from oddadmix/Nawah-Router-BERT-6M-v2: direct link, hf CLI and curl.
- Browser
- Download file 3.03 MB
-
https://huggingface.co/oddadmix/Nawah-Router-BERT-6M-v2/resolve/main/tokenizer.json
- Command line
-
hf download hf://oddadmix/Nawah-Router-BERT-6M-v2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/oddadmix/Nawah-Router-BERT-6M-v2/resolve/main/tokenizer.json
3.03 MB
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