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