Feature Extraction
Transformers
Safetensors
English
Korean
multilingual
qwen3_vl
vision-language
embedding
multimodal-embedding
mmeb
digital-forensics
custom_code
Instructions to use Urock-AI/Eddy-vl_embedding_1.9B_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Urock-AI/Eddy-vl_embedding_1.9B_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Urock-AI/Eddy-vl_embedding_1.9B_v1", trust_remote_code=True)# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Urock-AI/Eddy-vl_embedding_1.9B_v1", trust_remote_code=True) model = AutoModel.from_pretrained("Urock-AI/Eddy-vl_embedding_1.9B_v1", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
File size: 261 Bytes
c890b56 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | from .vision_process import (
extract_vision_info,
fetch_image,
fetch_video,
process_vision_info,
smart_resize,
)
__all__ = [
"extract_vision_info",
"fetch_image",
"fetch_video",
"process_vision_info",
"smart_resize",
]
|