diffusers

Running Stable diffusion model using Huggingface Diffusers in Torchserve.

Step 1: Download model

Set access token generated form Huggingface in Download_model.py file

Install dependencies

pip install -r requirements.txt

python Download_model.py

Step 2: Compress downloaded model

NOTE: Install Zip cli tool

Navigate back to model directory.

cd Diffusion_model
zip -r ../model.zip *

Step 3: Generate MAR file

Navigate up one level to diffusers directory.

torch-model-archiver --model-name stable-diffusion --version 1.0 --handler stable_diffusion_handler.py --extra-files model.zip -r requirements.txt

Step 4: Start torchserve

Update config.properties and start torchserve

torchserve --start --ts-config config.properties

Step 5: Run inference

python query.py --url "http://localhost:8080/predictions/stable-diffusion" --prompt "a photo of an astronaut riding a horse on mars"

The image generated will be written to a file output-20221027213010.jpg.

NOTE: For KServe implementation use the below inputs for v1 and v2 protocols. Kserve v1 protocol - sample_v1.json Kserve v2 protocol - sample_v2.json