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alighamdan/dreamlike-ai.ipynb

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dreamlike-ai.ipynb
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"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/alighamdan/c558caec0fb0b5bec249d9957e4d425e/dreamlike-ai.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"source": [
"# INSTALL DEPENDENCIES "
],
"metadata": {
"id": "Aek_U9pkmfYJ"
}
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "pGQaxtC2lxL7",
"outputId": "da89fdef-bbc3-4b1f-d543-5ff3ee9777f9"
},
"outputs": [],
"source": [
"! pip install gradio torch diffusers\n",
"! pip install transformers\n",
"! pip install accelerate"
]
},
{
"cell_type": "code",
"source": [
"from diffusers import StableDiffusionPipeline\n",
"import torch\n",
"from IPython.display import Image\n",
"\n",
"model_id = \"dreamlike-art/dreamlike-diffusion-1.0\" # can be: dreamlike-art/dreamlike-photoreal-1.0\n",
"pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16).to('cuda')"
],
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"colab": {
"base_uri": "https://localhost:8080/",
"height": 156,
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"source": [
"prompt = \"cute young girl with orange hair and red eyes with small smile\"\n",
"negative_prompt = \"\"\n",
"steps = 30\n",
"scale = 7.5\n",
"width = 768\n",
"height = 768\n",
"seed = 0\n",
"result = pipe(\n",
" prompt, \n",
" negative_prompt = negative_prompt, \n",
" num_inference_steps=steps, \n",
" guidance_scale = scale, \n",
" width=width, \n",
" height=height, \n",
" generator = torch.Generator('cuda').manual_seed(seed) if seed != 0 else None\n",
" )\n",
"\n",
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"\n",
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}
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