Model Details
Full Model IDgoogle/gemma-3-12b-it
Pipeline / Taskimage-text-to-text
Librarytransformers
Downloads (all-time)2.5M
Likes707
Last Modified3/21/2025
Author / Orggoogle
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="google/gemma-3-12b-it")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerssafetensorsgemma3image-text-to-textconversationalarxiv:1905.07830arxiv:1905.10044arxiv:1911.11641arxiv:1904.09728arxiv:1705.03551arxiv:1911.01547arxiv:1907.10641arxiv:1903.00161arxiv:2009.03300arxiv:2304.06364arxiv:2103.03874arxiv:2110.14168arxiv:2311.12022arxiv:2108.07732arxiv:2107.03374arxiv:2210.03057arxiv:2106.03193arxiv:1910.11856arxiv:2502.12404arxiv:2502.21228arxiv:2404.16816arxiv:2104.12756arxiv:2311.16502arxiv:2203.10244arxiv:2404.12390
More image-text-to-text Models
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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
⬇ Downloads2.5M
❤️ Community Likes707
🛠️ 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.