Model Details
Full Model IDgoogle/gemma-4-26B-A4B-it
Pipeline / Taskimage-text-to-text
Librarytransformers
Downloads (all-time)7.0M
Likes914
Last Modified5/7/2026
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-4-26B-A4B-it")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerssafetensorsgemma4image-text-to-textconversationalbase_model:google/gemma-4-26B-A4Bbase_model:finetune:google/gemma-4-26B-A4Blicense:apache-2.0eval-resultsendpoints_compatibledeploy:azureregion: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
⬇ Downloads7.0M
❤️ Community Likes914
🛠️ 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.