Text Classification
Transformers
Safetensors
Arabic
Stance Detection
Text Classification
arabic-nlp
stanceeval-2026
few-shot-learning
retrieval-augmented
Mawqif-v2
ensemble
LoRA
AraBERT
MARBERT
Instructions to use zaher-m/stanceeval2026 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zaher-m/stanceeval2026 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zaher-m/stanceeval2026")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("zaher-m/stanceeval2026", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download stacking_ensemble/probs/gemma4_t2_test.npy from zaher-m/stanceeval2026: direct link, hf CLI and curl.
- Browser
- Download file 15.6 kB
-
https://huggingface.co/zaher-m/stanceeval2026/resolve/main/stacking_ensemble/probs/gemma4_t2_test.npy
- Command line
-
hf download hf://zaher-m/stanceeval2026/stacking_ensemble/probs/gemma4_t2_test.npy
-
curl -L -o gemma4_t2_test.npy https://huggingface.co/zaher-m/stanceeval2026/resolve/main/stacking_ensemble/probs/gemma4_t2_test.npy
15.6 kB
- Xet hash:
- 2da77b52c1fb3d81bfb2e46d7afee839a44a6fd8e6214de6566ef966caece52f
- Size of remote file:
- 15.6 kB
- SHA256:
- be4778d4d6e20309cdf7054992640d0c1ee2bbd6890e286125afb249762484b0
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