Model Details
Full Model IDomlab/VLX-Seek-1.5-10B
Pipeline / Taskimage-text-to-text
Librarytransformers
Downloads (all-time)182.2K
Likes26
Last Modified7/23/2026
Author / Orgomlab
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("image-text-to-text", model="omlab/VLX-Seek-1.5-10B")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerssafetensorsvlx_seek_1_5text-generationvlxobject-detectiongroundingmultimodalRECVLMzero-shot-object-detectionimage-text-to-textconversationalzhenlicense:apache-2.0endpoints_compatibleregion:us
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: image-text-to-text
This model is designed for the image-text-to-text task. Explore more models for this use case.
All image-text-to-text Models →📊 Popularity
⬇ Downloads182.2K
❤️ Community Likes26
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.