Model Details
Full Model IDnvidia/LocateAnything-3B
Pipeline / Taskimage-text-to-text
Librarytransformers
Downloads (all-time)728.3K
Likes2.5K
Last Modified6/12/2026
Author / Orgnvidia
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="nvidia/LocateAnything-3B")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerssafetensorslocateanythingfeature-extractionnvidiaeaglevisionobject-detectiongroundingarxiv:2605.27365image-text-to-textconversationalcustom_codeenarxiv:2504.07491arxiv:2109.10852arxiv:2510.12798arxiv:2303.05499arxiv:1405.0312arxiv:1908.03195arxiv:2504.07981base_model:Qwen/Qwen2.5-3B-Instructbase_model:finetune:Qwen/Qwen2.5-3B-Instructlicense:otherregion:us
More image-text-to-text Models
See all →🚀 Use This Model
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
⬇ Downloads728.3K
❤️ Community Likes2.5K
🛠️ 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.