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:
- e64157de7bb23287719361fc728ef8831787a4970ae9b19726b2a2eb9596f870
- Size of remote file:
- 4.99 GB
- SHA256:
- b2bbef4d52ad6a9599bc3b258648c6a4af7f51a14cad853eda0773e1c90ba02d
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