Visual Document Retrieval
Transformers
Safetensors
ColPali
ops_colqwen3
feature-extraction
multimodal_embedding
embedding
multilingual-embedding
colqwen3
custom_code
Instructions to use OpenSearch-AI/Ops-Colqwen3-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenSearch-AI/Ops-Colqwen3-4B with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenSearch-AI/Ops-Colqwen3-4B", trust_remote_code=True, device_map="auto") - ColPali
How to use OpenSearch-AI/Ops-Colqwen3-4B 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: 435 Bytes
4894b7d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | from transformers import Qwen3VLConfig
class OpsColQwen3Config(Qwen3VLConfig):
"""
Configuration class for OpsColQwen3 model.
"""
model_type = "ops_colqwen3"
def __init__(
self,
dims: int = 2560,
mask_non_image_embeddings: bool = False,
**kwargs
):
super().__init__(**kwargs)
self.dims = dims
self.mask_non_image_embeddings = mask_non_image_embeddings
|