Visual Document Retrieval
Transformers
Safetensors
ColPali
multilingual
colvec1
feature-extraction
text
image
video
multimodal-embedding
vidore
colqwen3_5
multilingual-embedding
custom_code
Instructions to use webAI-Official/webAI-ColVec1-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use webAI-Official/webAI-ColVec1-4b with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("webAI-Official/webAI-ColVec1-4b", trust_remote_code=True, dtype="auto") - ColPali
How to use webAI-Official/webAI-ColVec1-4b with ColPali:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 794 Bytes
52a092a | 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 | """
Configuration for ColVec1 retrieval model.
"""
from transformers.configuration_utils import PretrainedConfig
class ColVec1Config(PretrainedConfig):
"""Configuration for the ColVec1 retrieval wrapper."""
model_type = "colvec1"
def __init__(
self,
embed_dim: int = 128,
text_hidden_size: int = 2560,
padding_side: str = "left",
initializer_range: float = 0.02,
base_model_name_or_path: str = None,
**kwargs,
):
super().__init__(**kwargs)
self.embed_dim = embed_dim
self.text_hidden_size = text_hidden_size
self.padding_side = padding_side
self.initializer_range = initializer_range
self.base_model_name_or_path = base_model_name_or_path
__all__ = ["ColVec1Config"]
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