Fill-Mask
Transformers
Safetensors
Arabic
bert_hash_v2
bert
arabic
masked-language-modeling
encoder
custom_code
berthash
research
Instructions to use Waqf-AI/arabic-berthash-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Waqf-AI/arabic-berthash-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Waqf-AI/arabic-berthash-v2", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Waqf-AI/arabic-berthash-v2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add architecture visualization and replace model-card tables with accessible SVG panels
8b2032c verified |
Download assets/model-architecture.svg from Waqf-AI/arabic-berthash-v2: direct link, hf CLI and curl.
- Browser
- Download file 3.24 kB
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https://huggingface.co/Waqf-AI/arabic-berthash-v2/resolve/main/assets/model-architecture.svg
- Command line
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hf download hf://Waqf-AI/arabic-berthash-v2/assets/model-architecture.svg
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curl -L -o model-architecture.svg https://huggingface.co/Waqf-AI/arabic-berthash-v2/resolve/main/assets/model-architecture.svg
3.24 kB