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
| 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", | |
| ] | |