Feature Extraction
Transformers
Safetensors
Arabic
embedding_gemma2
arabic
ocr
document-ai
word-matching
multimodal-embedding
embeddinggemma
Instructions to use g3ida/ArabicWordsEmbedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use g3ida/ArabicWordsEmbedding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="g3ida/ArabicWordsEmbedding")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("g3ida/ArabicWordsEmbedding") model = AutoModel.from_pretrained("g3ida/ArabicWordsEmbedding", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 238 Bytes
e7a8573 | 1 2 3 4 5 6 7 | {
"image_height": 96,
"max_soft_tokens": 70,
"text_prompt": null,
"text_normalisation": "arabic.core_word (strip tashkeel + edge punctuation)",
"note": "use scripts/match_page.py (embed.patchify(height=96)) for image preprocessing"
} |