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")# pip install -U transformers accelerate # 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 router_model.pt from oddadmix/Nawah-Router-v3: direct link, hf CLI and curl.
- Browser
- Download file 208 MB
-
https://huggingface.co/oddadmix/Nawah-Router-v3/resolve/main/router_model.pt
- Command line
-
hf download hf://oddadmix/Nawah-Router-v3/router_model.pt
-
curl -L -o router_model.pt https://huggingface.co/oddadmix/Nawah-Router-v3/resolve/main/router_model.pt
208 MB
- Xet hash:
- e68fa77874c82aab0e3f0ce32f25bf36c8bf87d8bfd043cb51fbecf657e46f37
- Size of remote file:
- 208 MB
- SHA256:
- 90ff8180f65ed7ae63a3445b5418bf3f35ea051816e6f7ff367450da44a7c0fc
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