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:
# pip install -U transformers accelerate # 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
Download tokenizer.json from OpenSearch-AI/Ops-Colqwen3-4B: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/OpenSearch-AI/Ops-Colqwen3-4B/resolve/refs%2Fpr%2F5/tokenizer.json
- Command line
-
hf download hf://OpenSearch-AI/Ops-Colqwen3-4B@refs/pr/5/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/OpenSearch-AI/Ops-Colqwen3-4B/resolve/refs%2Fpr%2F5/tokenizer.json
11.4 MB
- Xet hash:
- 693ec4b3922b0bd306bf7b4989e115ffbfeb7b0c08b31bc6d956818c6bb07f61
- Size of remote file:
- 11.4 MB
- SHA256:
- aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
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