title | emoji | colorFrom | colorTo | sdk | sdk_version | app_file | pinned | license |
---|---|---|---|---|---|---|---|---|
NGC5128 SDXL |
🫓🥽 |
blue |
purple |
gradio |
4.31.5 |
app.py |
false |
creativeml-openrail-m |
🚀Check out the configuration reference at : https://huggingface.co/docs/hub/spaces-config-reference
🚀Huggingface space : https://huggingface.co/spaces/prithivMLmods/NGC5128-StableDiffusion-XL
🚀The GitHub Model Workspace :
# Make sure you have git-lfs installed (https://git-lfs.com)
git lfs install
git clone https://huggingface.co/spaces/prithivMLmods/NGC5128-StableDiffusion-XL
# If you want to clone without large files - just their pointers
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/spaces/prithivMLmods/NGC5128-StableDiffusion-XL
ℹ️Generated Result in Huggingface Spaces:
Prompt 1
Fashion shoot, Jacquemus and moncler collaboration: light pink translucent fur sneakers, hyper-realistic, detailed 8k, realistic.
prompt 2
a painting of an eye with purple and orange flowers, in the style of james jean, mysterious jungle, martin ansin, 32k uhd, papua new guinea art, light blue and red, poster --ar 37:61 --stylize 750 --v 6
prompt 3
(Pirate ship sailing into a bioluminescence sea with a galaxy in the sky), epic, 4k, ultra,
prompt 4
front view, capture a urban style, Hoodie, technical materials, fabric small point label on text 'Graytheory', the design is minimal, with a raised collar, fabric is a dark grey, low angle to capture the Hoodie's form and detailing, f/5.6 to focus on the hoodie's craftsmanship, solid grey background, studio light setting
gradio
gradio-client
import requests
API_URL = "https://api-inference.huggingface.co/models/prithivMLmods/NGC5128-StableDiffusion-XL-v4"
headers = {"Authorization": "Bearer xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"}
def query(payload):
response = requests.post(API_URL, headers=headers, json=payload)
return response.content
image_bytes = query({
"inputs": "Astronaut riding a horse",
})
# You can access the image with PIL.Image for example
import io
from PIL import Image
image = Image.open(io.BytesIO(image_bytes))
.
.
.
.