Model Details
Full Model IDgoogle/gemma-4-E4B-it-qat-q4_0-gguf
Pipeline / Taskany-to-any
Library—
Downloads (all-time)968.9K
Likes167
Last Modified7/17/2026
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("any-to-any", model="google/gemma-4-E4B-it-qat-q4_0-gguf")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
ggufany-to-anyarxiv:2607.02770base_model:google/gemma-4-E4B-it-qat-q4_0-unquantizedbase_model:quantized:google/gemma-4-E4B-it-qat-q4_0-unquantizedlicense:apache-2.0endpoints_compatibleregion:usconversational
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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: any-to-any
This model is designed for the any-to-any task. Explore more models for this use case.
All any-to-any Models →📊 Popularity
⬇ Downloads968.9K
❤️ Community Likes167
🛠️ Requirements
- →Check docs for installation steps.
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.