Model Details
Full Model IDcyankiwi/gemma-4-26B-A4B-it-AWQ-4bit
Pipeline / Taskimage-text-to-text
Librarytransformers
Downloads (all-time)2.6M
Likes94
Last Modified7/21/2026
Author / Orgcyankiwi
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="cyankiwi/gemma-4-26B-A4B-it-AWQ-4bit")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerssafetensorsgemma4image-text-to-textconversationalbase_model:google/gemma-4-26B-A4B-itbase_model:quantized:google/gemma-4-26B-A4B-itlicense:apache-2.0endpoints_compatiblecompressed-tensorsregion:us
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
⬇ Downloads2.6M
❤️ Community Likes94
🛠️ 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.