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
Download tokenizer.json from oddadmix/Nawah-Router-v3: direct link, hf CLI and curl.
- Browser
- Download file 3.02 MB
-
https://huggingface.co/oddadmix/Nawah-Router-v3/resolve/main/tokenizer.json
- Command line
-
hf download hf://oddadmix/Nawah-Router-v3/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/oddadmix/Nawah-Router-v3/resolve/main/tokenizer.json
3.02 MB
File too large to display, you can check the raw version instead.