📄 About This Model
FP8-Block variant of gemma-4-31B-it.
Model Details
Full Model IDRedHatAI/gemma-4-31B-it-FP8-block
Pipeline / Taskimage-text-to-text
Librarytransformers
Downloads (all-time)972.6K
Likes45
Last Modified8/13/2026
Author / OrgRedHatAI
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="RedHatAI/gemma-4-31B-it-FP8-block")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerssafetensorsgemma4image-text-to-textfp8vllmllm-compressorcompressed-tensorsconversationalbase_model:google/gemma-4-31B-itbase_model:quantized:google/gemma-4-31B-itlicense:apache-2.0endpoints_compatibledeploy:sagemakerregion: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
⬇ Downloads972.6K
❤️ Community Likes45
🛠️ 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.