Feature Extraction
Transformers
Safetensors
qwen3_5
image-text-to-text
multimodal
text
image
video
visual-document
embedding
retrieval
Instructions to use ATH-MaaS/Ovis-VL-Embedding-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ATH-MaaS/Ovis-VL-Embedding-9B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ATH-MaaS/Ovis-VL-Embedding-9B")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("ATH-MaaS/Ovis-VL-Embedding-9B") model = AutoModelForMultimodalLM.from_pretrained("ATH-MaaS/Ovis-VL-Embedding-9B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download ovis_embedding_train_inference.png from ATH-MaaS/Ovis-VL-Embedding-9B: direct link, hf CLI and curl.
- Browser
- Download file 414 kB
-
https://huggingface.co/ATH-MaaS/Ovis-VL-Embedding-9B/resolve/ca6d5db2738e88f61476e771f4bef1572dee088b/ovis_embedding_train_inference.png
- Command line
-
hf download hf://ATH-MaaS/Ovis-VL-Embedding-9B@ca6d5db2738e88f61476e771f4bef1572dee088b/ovis_embedding_train_inference.png
-
curl -L -o ovis_embedding_train_inference.png https://huggingface.co/ATH-MaaS/Ovis-VL-Embedding-9B/resolve/ca6d5db2738e88f61476e771f4bef1572dee088b/ovis_embedding_train_inference.png
414 kB

- Xet hash:
- 8033828cfe208c85d16d5e1ae6b93f02fbe9d19297cdc6c7d2e5c5cbe61d1571
- Size of remote file:
- 414 kB
- SHA256:
- 49353acc8881c8186a5aa48642451e58e706cf71fc4aa8ba3414fad8007933d9
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