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: 836 Bytes
c890b56 760cac6 c890b56 760cac6 c890b56 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | {
"auto_map": {
"AutoProcessor": "processing_vl.VLProcessor"
},
"add_prefix_space": false,
"backend": "tokenizers",
"bos_token": null,
"clean_up_tokenization_spaces": false,
"eos_token": "<|im_end|>",
"errors": "replace",
"extra_special_tokens": [
"<|im_start|>",
"<|im_end|>",
"<|object_ref_start|>",
"<|object_ref_end|>",
"<|box_start|>",
"<|box_end|>",
"<|quad_start|>",
"<|quad_end|>",
"<|vision_start|>",
"<|vision_end|>",
"<|vision_pad|>",
"<|image_pad|>",
"<|video_pad|>"
],
"is_local": true,
"model_max_length": 262144,
"model_specific_special_tokens": {},
"pad_token": "<|endoftext|>",
"padding_side": "right",
"processor_class": "VLProcessor",
"split_special_tokens": false,
"tokenizer_class": "Qwen2Tokenizer",
"unk_token": null
}
|