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import streamlit as st
x = st.slider('Select a value')
st.write(x, 'squared is', x * x)
from diffusers import DiffusionPipeline
import torch
pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float32, use_safetensors=True, variant="fp32")
# if using torch < 2.0
# pipe.enable_xformers_memory_efficient_attention()
prompt = "An astronaut riding a green horse"
images = pipe(prompt=prompt).images[0]
st.image(images)
st.write("hello")
"""
import json
import requests
API_URL = "https://api-inference.huggingface.co/models/gpt2"
token = "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"
headers = {"Authorization": f"Bearer {token}"}
def query(payload):
data = json.dumps(payload)
response = requests.request("POST", API_URL, headers=headers, data=data)
return json.loads(response.content.decode("utf-8"))
data = query("Can you please let us know more details about your ")
print(data)
""" |