Instructions to use OzzyGT/ERNIE_Image_sdnq_dynamic_int4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use OzzyGT/ERNIE_Image_sdnq_dynamic_int4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OzzyGT/ERNIE_Image_sdnq_dynamic_int4", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
license: apache-2.0
base_model: Baidu/ERNIE-Image
pipeline_tag: text-to-image
library_name: diffusers
tags:
- text-to-image
- diffusers
- safetensors
- ernie-image
- sdnq
- quantized
ERNIE-Image SDNQ Dynamic INT4
This is an int4 quantized version of Baidu/ERNIE-Image using SDNQ (SD.Next Quantization) with the dynamic option.
Usage
You can find ready-to-use scripts in the diffusers-recipes repository.