Visual Document Retrieval
Transformers
Safetensors
ColPali
multilingual
colqwen3
feature-extraction
text
image
video
multimodal-embedding
vidore
multilingual-embedding
custom_code
Instructions to use TomoroAI/tomoro-colqwen3-embed-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TomoroAI/tomoro-colqwen3-embed-4b with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TomoroAI/tomoro-colqwen3-embed-4b", trust_remote_code=True, device_map="auto") - ColPali
How to use TomoroAI/tomoro-colqwen3-embed-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
- Xet hash:
- 270d4d5e6e15a0b23c2f6f4d3f7dff690f8df32e9528e7563a09a433c8a64acf
- Size of remote file:
- 3.89 GB
- SHA256:
- d66588ac9aef215ca72a47ce1cd2b89b3253085ccafe4ca06e754fc50e757ac7
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