1_experimentation.ipynb

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    "# Experimenting with Text to Image Generation\n",
    "\n",
    "In this notebook, we'll experiment with generative AI using a text-to-image model called stable diffusion.  We'll be using an open source [model](https://huggingface.co/runwayml/stable-diffusion-v1-5) from [Huggingface](huggingface.co)"
   ]
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check GPU\n",
    "\n",
    "While we can run these notebooks without a GPU, it'll be much faster with one.  Let's check to make sure we have a GPU and how much memory we have available."
   ]
  },
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    "outputId": "eb1aafed-5079-4048-d49f-7d9990efd48d",
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   "source": [
    "!nvidia-smi --query-gpu=name,memory.total,memory.free --format=csv,noheader"
   ]
  },
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   "source": [
    "### Install Libraries\n",
    "\n",
    "We need some libraries to run the diffusion pipeline.  The most important is the [Huggingface Diffusers library](https://huggingface.co/docs/diffusers/index)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
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   "outputs": [],
   "source": [
    "!pip install -r requirements.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "!pip list | grep -E \"boto|grpcio|pandas|torch|torchvision|diffusers|transformers|accelerate|flash-attn|ftfy|xformers|protobuf|bitsandbytes\""
   ]
  },
  {
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   "source": [
    "### Load the Pre-Trained Model\n",
    "\n",
    "We can load a pre-trained model directly from Huggingface.  Here we're specifying [stabilityai/stable-diffusion-2-1](https://huggingface.co/stabilityai/stable-diffusion-2-1), but we could also have used any number of models including [runwayml/stable-diffusion-v1-5](runwayml/stable-diffusion-v1-5) or [CompVis/stable-diffusion-v1-4](https://huggingface.co/CompVis/stable-diffusion-v1-4)\n",
    "\n",
    "[model](https://huggingface.co/stabilityai/stable-diffusion-2-1)\n",
    "\n",
    "```\n",
    "DiffusionPipeline.from_pretrained(\"stabilityai/stable-diffusion-2-1\")\n",
    "```"
   ]
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   "source": [
    "import torch\n",
    "from diffusers import DiffusionPipeline\n",
    "\n",
    "# load the model from Huggingface\n",
    "pipeline = DiffusionPipeline.from_pretrained(\"stabilityai/stable-diffusion-2-1\")\n",
    "\n",
    "# You could also load local weights:\n",
    "# pipeline = DiffusionPipeline.from_pretrained(\"./notebook-output/stable_diffusion_weights/redhat-dog\")\n",
    "\n",
    "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
    "pipeline.to(device)"
   ]
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   "source": [
    "## Sample Inference"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### A Dog"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "image = pipeline(\"a photo of a dog\",\n",
    "                 negative_prompt=\"ugly, deformed, bad anatomy\").images[0]\n",
    "image"
   ]
  },
  {
   "cell_type": "markdown",
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   },
   "source": [
    "### Not My Dog\n",
    "\n",
    "So, I know of a specific dog I want to generate pictures of.\n",
    "\n",
    "This is my `rhteddy` dog:\n",
    "\n",
    "![redhat dog](https://rhods-public.s3.amazonaws.com/sample-data/images/redhat-dog-small.jpg)\n",
    "\n",
    "Let's try and generate a picture of Red Hat Teddy."
   ]
  },
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    "\n",
    "\n",
    "image = pipeline(\"a photo of a rhteddy dog\").images[0]\n",
    "image"
   ]
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### My Dog\n",
    "\n",
    "As you can tell, we generated a picture, but it wasn't my dog.\n",
    "\n",
    "The word `rhteddy`, means nothing to the model, or to you, either.  In order to teach the model about Teddy, I'll have to fine tune it\n",
    "\n",
    "[Notebook 2 - Fine Tuning](2_fine_tuning_custom.ipynb)\n"
   ]
  }
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