Visual Document Retrieval
PEFT
Safetensors
vidore
multimodal_embedding
multilingual_embedding
Text-to-Visual Document (T→VD) retrieval
Instructions to use Metric-AI/ColQwen2.5-3b-multilingual-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Metric-AI/ColQwen2.5-3b-multilingual-v1.0 with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
File size: 564 Bytes
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{
"idx": 0,
"name": "0",
"path": "",
"type": "sentence_transformers.base.modules.transformer.Transformer"
},
{
"idx": 1,
"name": "1",
"path": "1_Dense",
"type": "sentence_transformers.base.modules.dense.Dense"
},
{
"idx": 2,
"name": "2",
"path": "2_Normalize",
"type": "sentence_transformers.base.modules.normalize.Normalize"
},
{
"idx": 3,
"name": "3",
"path": "3_MultiVectorMask",
"type": "sentence_transformers.multi_vector_encoder.modules.multi_vector_mask.MultiVectorMask"
}
]
|