diff --git a/diffusers/asymetric_tiling.ipynb b/diffusers/asymetric_tiling.ipynb
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--- /dev/null
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Asymmetric tiling\n",
+    "\n",
+    "Stable Diffusion is not trained to generate seamless textures. However, you can use this simple script to add tiling to your generation. This script is contributed by [alexisrolland](https://github.com/alexisrolland). See more details in the [this issue](https://github.com/huggingface/diffusers/issues/556)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: diffusers in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (0.31.0)\n",
+      "Requirement already satisfied: torch in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (2.2.1+cu121)\n",
+      "Requirement already satisfied: accelerate in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (1.1.1)\n",
+      "Requirement already satisfied: transformers in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (4.46.2)\n",
+      "Requirement already satisfied: importlib-metadata in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (8.5.0)\n",
+      "Requirement already satisfied: filelock in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (3.16.1)\n",
+      "Requirement already satisfied: huggingface-hub>=0.23.2 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (0.26.2)\n",
+      "Requirement already satisfied: numpy in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (1.26.4)\n",
+      "Requirement already satisfied: regex!=2019.12.17 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (2024.11.6)\n",
+      "Requirement already satisfied: requests in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (2.32.3)\n",
+      "Requirement already satisfied: safetensors>=0.3.1 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (0.4.5)\n",
+      "Requirement already satisfied: Pillow in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (11.0.0)\n",
+      "Requirement already satisfied: typing-extensions>=4.8.0 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (4.12.2)\n",
+      "Requirement already satisfied: sympy in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (1.13.3)\n",
+      "Requirement already satisfied: networkx in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (3.4.2)\n",
+      "Requirement already satisfied: jinja2 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (3.1.4)\n",
+      "Requirement already satisfied: fsspec in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (2024.10.0)\n",
+      "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.1.105 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (12.1.105)\n",
+      "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.1.105 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (12.1.105)\n",
+      "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.1.105 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (12.1.105)\n",
+      "Requirement already satisfied: nvidia-cudnn-cu12==8.9.2.26 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (8.9.2.26)\n",
+      "Requirement already satisfied: nvidia-cublas-cu12==12.1.3.1 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (12.1.3.1)\n",
+      "Requirement already satisfied: nvidia-cufft-cu12==11.0.2.54 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (11.0.2.54)\n",
+      "Requirement already satisfied: nvidia-curand-cu12==10.3.2.106 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (10.3.2.106)\n",
+      "Requirement already satisfied: nvidia-cusolver-cu12==11.4.5.107 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (11.4.5.107)\n",
+      "Requirement already satisfied: nvidia-cusparse-cu12==12.1.0.106 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (12.1.0.106)\n",
+      "Requirement already satisfied: nvidia-nccl-cu12==2.19.3 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (2.19.3)\n",
+      "Requirement already satisfied: nvidia-nvtx-cu12==12.1.105 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (12.1.105)\n",
+      "Requirement already satisfied: triton==2.2.0 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (2.2.0)\n",
+      "Requirement already satisfied: nvidia-nvjitlink-cu12 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from nvidia-cusolver-cu12==11.4.5.107->torch) (12.6.77)\n",
+      "Requirement already satisfied: packaging>=20.0 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from accelerate) (24.1)\n",
+      "Requirement already satisfied: psutil in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from accelerate) (6.1.0)\n",
+      "Requirement already satisfied: pyyaml in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from accelerate) (6.0.2)\n",
+      "Requirement already satisfied: tokenizers<0.21,>=0.20 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from transformers) (0.20.3)\n",
+      "Requirement already satisfied: tqdm>=4.27 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from transformers) (4.66.6)\n",
+      "Requirement already satisfied: zipp>=3.20 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from importlib-metadata->diffusers) (3.21.0)\n",
+      "Requirement already satisfied: MarkupSafe>=2.0 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from jinja2->torch) (3.0.2)\n",
+      "Requirement already satisfied: charset-normalizer<4,>=2 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from requests->diffusers) (3.4.0)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from requests->diffusers) (3.10)\n",
+      "Requirement already satisfied: urllib3<3,>=1.21.1 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from requests->diffusers) (2.2.3)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from requests->diffusers) (2024.8.30)\n",
+      "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from sympy->torch) (1.3.0)\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip install diffusers torch accelerate transformers"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "from typing import Optional\n",
+    "from diffusers import StableDiffusionPipeline\n",
+    "from diffusers.models.lora import LoRACompatibleConv\n",
+    "\n",
+    "def seamless_tiling(pipeline, x_axis, y_axis):\n",
+    "    def asymmetric_conv2d_convforward(self, input: torch.Tensor, weight: torch.Tensor, bias: Optional[torch.Tensor] = None):\n",
+    "        self.paddingX = (self._reversed_padding_repeated_twice[0], self._reversed_padding_repeated_twice[1], 0, 0)\n",
+    "        self.paddingY = (0, 0, self._reversed_padding_repeated_twice[2], self._reversed_padding_repeated_twice[3])\n",
+    "        working = torch.nn.functional.pad(input, self.paddingX, mode=x_mode)\n",
+    "        working = torch.nn.functional.pad(working, self.paddingY, mode=y_mode)\n",
+    "        return torch.nn.functional.conv2d(working, weight, bias, self.stride, torch.nn.modules.utils._pair(0), self.dilation, self.groups)\n",
+    "    x_mode = 'circular' if x_axis else 'constant'\n",
+    "    y_mode = 'circular' if y_axis else 'constant'\n",
+    "    targets = [pipeline.vae, pipeline.text_encoder, pipeline.unet]\n",
+    "    convolution_layers = []\n",
+    "    for target in targets:\n",
+    "        for module in target.modules():\n",
+    "            if isinstance(module, torch.nn.Conv2d):\n",
+    "                convolution_layers.append(module)\n",
+    "    for layer in convolution_layers:\n",
+    "        if isinstance(layer, LoRACompatibleConv) and layer.lora_layer is None:\n",
+    "            layer.lora_layer = lambda * x: 0\n",
+    "        layer._conv_forward = asymmetric_conv2d_convforward.__get__(layer, torch.nn.Conv2d)\n",
+    "    return pipeline\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1fe7c93d4c284a3dbea050bb32b4fdbb",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "model_index.json:   0%|          | 0.00/541 [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "800df14452064af0a3b5b350bcff79b3",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Fetching 15 files:   0%|          | 0/15 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "035b3e663c9b4645a1849e4e44ad18d2",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "(…)ature_extractor/preprocessor_config.json:   0%|          | 0.00/342 [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "5365d546370d4c62bf2d43b95f989a1a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "tokenizer/merges.txt:   0%|          | 0.00/525k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "84a7505fdf7644898774be25a69ba8a0",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "text_encoder/config.json:   0%|          | 0.00/617 [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8f5e0949ad264122a95f7a9f3fc6a592",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "tokenizer/special_tokens_map.json:   0%|          | 0.00/472 [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "7154fe0ee6964d4dabd7faad9ab2f91e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "model.safetensors:   0%|          | 0.00/1.22G [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e3445255cac2477dab44e7637ed78bd2",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "model.safetensors:   0%|          | 0.00/492M [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a6814bb5f88c42e8a16d627d3414dffa",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "scheduler/scheduler_config.json:   0%|          | 0.00/308 [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "de3e32d444b140dc88cec7205e7d20f8",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "safety_checker/config.json:   0%|          | 0.00/4.72k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d38e12cc00ee4175b6ac61934c50a790",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "tokenizer/tokenizer_config.json:   0%|          | 0.00/806 [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e6ef50cc68f0495a8ab0a859aa8846c6",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "unet/config.json:   0%|          | 0.00/743 [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "fd2df9b13391492b81ebaabada3564a9",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "tokenizer/vocab.json:   0%|          | 0.00/1.06M [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e61f198fcefe470b997a5368f6d6a432",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "diffusion_pytorch_model.safetensors:   0%|          | 0.00/3.44G [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "7626726676ed4f9686ea710b846f8e9d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "vae/config.json:   0%|          | 0.00/547 [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2b880f94671b4192a92f97d6cd42cdf6",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "diffusion_pytorch_model.safetensors:   0%|          | 0.00/335M [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "7ce11626fd054518921ca192b52cea6b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Loading pipeline components...:   0%|          | 0/7 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "317e981c67ea4533929bba0bbbb34e44",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/20 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pipeline = StableDiffusionPipeline.from_pretrained(\"stable-diffusion-v1-5/stable-diffusion-v1-5\", torch_dtype=torch.float16, use_safetensors=True)\n",
+    "pipeline.enable_model_cpu_offload()\n",
+    "prompt = [\"texture of a red brick wall\"]\n",
+    "seed = 123456\n",
+    "generator = torch.Generator(device='cuda').manual_seed(seed)\n",
+    "\n",
+    "pipeline = seamless_tiling(pipeline=pipeline, x_axis=True, y_axis=True)\n",
+    "image = pipeline(\n",
+    "    prompt=prompt,\n",
+    "    width=512,\n",
+    "    height=512,\n",
+    "    num_inference_steps=20,\n",
+    "    guidance_scale=7,\n",
+    "    num_images_per_prompt=1,\n",
+    "    generator=generator\n",
+    ").images[0]\n",
+    "seamless_tiling(pipeline=pipeline, x_axis=False, y_axis=False)\n",
+    "\n",
+    "torch.cuda.empty_cache()\n",
+    "image.save('image.png')"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/diffusers/ip_adapter_negative_noise.ipynb b/diffusers/ip_adapter_negative_noise.ipynb
new file mode 100644
index 00000000..de82415d
--- /dev/null
+++ b/diffusers/ip_adapter_negative_noise.ipynb
@@ -0,0 +1,294 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# IP Adapter Negative Noise\n",
+    "\n",
+    "Diffusers pipelines are fully integrated with IP-Adapter, which allows you to prompt the diffusion model with an image. However, it does not support negative image prompts (there is no negative_ip_adapter_image argument) the same way it supports negative text prompts. When you pass an ip_adapter_image, it will create a zero-filled tensor as a negative image. This script shows you how to create a negative noise from ip_adapter_image and use it to significantly improve the generation quality while preserving the composition of images.\n",
+    "\n",
+    "[cubiq](https://github.com/cubiq) initially developed this feature in his [repository](https://github.com/cubiq/ComfyUI_IPAdapter_plus). The community script was contributed by [asomoza](https://github.com/Somoza). You can find more details about this experimentation [this discussion](https://github.com/huggingface/diffusers/discussions/7167)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: diffusers in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (0.31.0)\n",
+      "Requirement already satisfied: torch in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (2.2.1+cu121)\n",
+      "Requirement already satisfied: accelerate in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (1.1.1)\n",
+      "Requirement already satisfied: transformers in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (4.46.2)\n",
+      "Requirement already satisfied: importlib-metadata in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (8.5.0)\n",
+      "Requirement already satisfied: filelock in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (3.16.1)\n",
+      "Requirement already satisfied: huggingface-hub>=0.23.2 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (0.26.2)\n",
+      "Requirement already satisfied: numpy in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (1.26.4)\n",
+      "Requirement already satisfied: regex!=2019.12.17 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (2024.11.6)\n",
+      "Requirement already satisfied: requests in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (2.32.3)\n",
+      "Requirement already satisfied: safetensors>=0.3.1 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (0.4.5)\n",
+      "Requirement already satisfied: Pillow in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (11.0.0)\n",
+      "Requirement already satisfied: typing-extensions>=4.8.0 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (4.12.2)\n",
+      "Requirement already satisfied: sympy in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (1.13.3)\n",
+      "Requirement already satisfied: networkx in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (3.4.2)\n",
+      "Requirement already satisfied: jinja2 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (3.1.4)\n",
+      "Requirement already satisfied: fsspec in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (2024.10.0)\n",
+      "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.1.105 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (12.1.105)\n",
+      "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.1.105 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (12.1.105)\n",
+      "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.1.105 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (12.1.105)\n",
+      "Requirement already satisfied: nvidia-cudnn-cu12==8.9.2.26 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (8.9.2.26)\n",
+      "Requirement already satisfied: nvidia-cublas-cu12==12.1.3.1 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (12.1.3.1)\n",
+      "Requirement already satisfied: nvidia-cufft-cu12==11.0.2.54 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (11.0.2.54)\n",
+      "Requirement already satisfied: nvidia-curand-cu12==10.3.2.106 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (10.3.2.106)\n",
+      "Requirement already satisfied: nvidia-cusolver-cu12==11.4.5.107 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (11.4.5.107)\n",
+      "Requirement already satisfied: nvidia-cusparse-cu12==12.1.0.106 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (12.1.0.106)\n",
+      "Requirement already satisfied: nvidia-nccl-cu12==2.19.3 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (2.19.3)\n",
+      "Requirement already satisfied: nvidia-nvtx-cu12==12.1.105 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (12.1.105)\n",
+      "Requirement already satisfied: triton==2.2.0 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (2.2.0)\n",
+      "Requirement already satisfied: nvidia-nvjitlink-cu12 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from nvidia-cusolver-cu12==11.4.5.107->torch) (12.6.77)\n",
+      "Requirement already satisfied: packaging>=20.0 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from accelerate) (24.1)\n",
+      "Requirement already satisfied: psutil in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from accelerate) (6.1.0)\n",
+      "Requirement already satisfied: pyyaml in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from accelerate) (6.0.2)\n",
+      "Requirement already satisfied: tokenizers<0.21,>=0.20 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from transformers) (0.20.3)\n",
+      "Requirement already satisfied: tqdm>=4.27 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from transformers) (4.66.6)\n",
+      "Requirement already satisfied: zipp>=3.20 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from importlib-metadata->diffusers) (3.21.0)\n",
+      "Requirement already satisfied: MarkupSafe>=2.0 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from jinja2->torch) (3.0.2)\n",
+      "Requirement already satisfied: charset-normalizer<4,>=2 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from requests->diffusers) (3.4.0)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from requests->diffusers) (3.10)\n",
+      "Requirement already satisfied: urllib3<3,>=1.21.1 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from requests->diffusers) (2.2.3)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from requests->diffusers) (2024.8.30)\n",
+      "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from sympy->torch) (1.3.0)\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip install diffusers torch accelerate transformers"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "The cache for model files in Transformers v4.22.0 has been updated. Migrating your old cache. This is a one-time only operation. You can interrupt this and resume the migration later on by calling `transformers.utils.move_cache()`.\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8ed53bd6790c44ee8e75b52486e011f8",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "0it [00:00, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import torch\n",
+    "\n",
+    "from diffusers import AutoencoderKL, DPMSolverMultistepScheduler, StableDiffusionXLPipeline\n",
+    "from diffusers.models import ImageProjection\n",
+    "from diffusers.utils import load_image\n",
+    "\n",
+    "\n",
+    "def encode_image(\n",
+    "    image_encoder,\n",
+    "    feature_extractor,\n",
+    "    image,\n",
+    "    device,\n",
+    "    num_images_per_prompt,\n",
+    "    output_hidden_states=None,\n",
+    "    negative_image=None,\n",
+    "):\n",
+    "    dtype = next(image_encoder.parameters()).dtype\n",
+    "\n",
+    "    if not isinstance(image, torch.Tensor):\n",
+    "        image = feature_extractor(image, return_tensors=\"pt\").pixel_values\n",
+    "\n",
+    "    image = image.to(device=device, dtype=dtype)\n",
+    "    if output_hidden_states:\n",
+    "        image_enc_hidden_states = image_encoder(image, output_hidden_states=True).hidden_states[-2]\n",
+    "        image_enc_hidden_states = image_enc_hidden_states.repeat_interleave(num_images_per_prompt, dim=0)\n",
+    "\n",
+    "        if negative_image is None:\n",
+    "            uncond_image_enc_hidden_states = image_encoder(\n",
+    "                torch.zeros_like(image), output_hidden_states=True\n",
+    "            ).hidden_states[-2]\n",
+    "        else:\n",
+    "            if not isinstance(negative_image, torch.Tensor):\n",
+    "                negative_image = feature_extractor(negative_image, return_tensors=\"pt\").pixel_values\n",
+    "            negative_image = negative_image.to(device=device, dtype=dtype)\n",
+    "            uncond_image_enc_hidden_states = image_encoder(negative_image, output_hidden_states=True).hidden_states[-2]\n",
+    "\n",
+    "        uncond_image_enc_hidden_states = uncond_image_enc_hidden_states.repeat_interleave(num_images_per_prompt, dim=0)\n",
+    "        return image_enc_hidden_states, uncond_image_enc_hidden_states\n",
+    "    else:\n",
+    "        image_embeds = image_encoder(image).image_embeds\n",
+    "        image_embeds = image_embeds.repeat_interleave(num_images_per_prompt, dim=0)\n",
+    "        uncond_image_embeds = torch.zeros_like(image_embeds)\n",
+    "\n",
+    "        return image_embeds, uncond_image_embeds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "@torch.no_grad()\n",
+    "def prepare_ip_adapter_image_embeds(\n",
+    "    unet,\n",
+    "    image_encoder,\n",
+    "    feature_extractor,\n",
+    "    ip_adapter_image,\n",
+    "    do_classifier_free_guidance,\n",
+    "    device,\n",
+    "    num_images_per_prompt,\n",
+    "    ip_adapter_negative_image=None,\n",
+    "):\n",
+    "    if not isinstance(ip_adapter_image, list):\n",
+    "        ip_adapter_image = [ip_adapter_image]\n",
+    "\n",
+    "    if len(ip_adapter_image) != len(unet.encoder_hid_proj.image_projection_layers):\n",
+    "        raise ValueError(\n",
+    "            f\"`ip_adapter_image` must have same length as the number of IP Adapters. Got {len(ip_adapter_image)} images and {len(unet.encoder_hid_proj.image_projection_layers)} IP Adapters.\"\n",
+    "        )\n",
+    "\n",
+    "    image_embeds = []\n",
+    "    for single_ip_adapter_image, image_proj_layer in zip(\n",
+    "        ip_adapter_image, unet.encoder_hid_proj.image_projection_layers\n",
+    "    ):\n",
+    "        output_hidden_state = not isinstance(image_proj_layer, ImageProjection)\n",
+    "        single_image_embeds, single_negative_image_embeds = encode_image(\n",
+    "            image_encoder,\n",
+    "            feature_extractor,\n",
+    "            single_ip_adapter_image,\n",
+    "            device,\n",
+    "            1,\n",
+    "            output_hidden_state,\n",
+    "            negative_image=ip_adapter_negative_image,\n",
+    "        )\n",
+    "        single_image_embeds = torch.stack([single_image_embeds] * num_images_per_prompt, dim=0)\n",
+    "        single_negative_image_embeds = torch.stack([single_negative_image_embeds] * num_images_per_prompt, dim=0)\n",
+    "\n",
+    "        if do_classifier_free_guidance:\n",
+    "            single_image_embeds = torch.cat([single_negative_image_embeds, single_image_embeds])\n",
+    "            single_image_embeds = single_image_embeds.to(device)\n",
+    "\n",
+    "        image_embeds.append(single_image_embeds)\n",
+    "\n",
+    "    return image_embeds\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "4bec0e55fd884409a235a267a3787263",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Loading pipeline components...:   0%|          | 0/7 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "bbd2cbc4dc9f4a8bae8f630ead55e2d4",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/25 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "vae = AutoencoderKL.from_pretrained(\n",
+    "    \"madebyollin/sdxl-vae-fp16-fix\",\n",
+    "    torch_dtype=torch.float16,\n",
+    ").to(\"cuda\")\n",
+    "\n",
+    "pipeline = StableDiffusionXLPipeline.from_pretrained(\n",
+    "    \"RunDiffusion/Juggernaut-XL-v9\",\n",
+    "    torch_dtype=torch.float16,\n",
+    "    vae=vae,\n",
+    "    variant=\"fp16\",\n",
+    ").to(\"cuda\")\n",
+    "\n",
+    "pipeline.scheduler = DPMSolverMultistepScheduler.from_config(pipeline.scheduler.config)\n",
+    "pipeline.scheduler.config.use_karras_sigmas = True\n",
+    "\n",
+    "pipeline.load_ip_adapter(\n",
+    "    \"h94/IP-Adapter\",\n",
+    "    subfolder=\"sdxl_models\",\n",
+    "    weight_name=\"ip-adapter-plus_sdxl_vit-h.safetensors\",\n",
+    "    image_encoder_folder=\"models/image_encoder\",\n",
+    ")\n",
+    "pipeline.set_ip_adapter_scale(0.7)\n",
+    "\n",
+    "ip_image = load_image(\"https://github.com/huggingface/diffusers/assets/5442875/901d8bd8-7a59-4fe7-bda1-a0e0d6c7dffd\")\n",
+    "negative_ip_image = load_image(\"https://github.com/huggingface/diffusers/assets/5442875/901d8bd8-7a59-4fe7-bda1-a0e0d6c7dffd\")\n",
+    "\n",
+    "image_embeds = prepare_ip_adapter_image_embeds(\n",
+    "    unet=pipeline.unet,\n",
+    "    image_encoder=pipeline.image_encoder,\n",
+    "    feature_extractor=pipeline.feature_extractor,\n",
+    "    ip_adapter_image=[[ip_image]],\n",
+    "    do_classifier_free_guidance=True,\n",
+    "    device=\"cuda\",\n",
+    "    num_images_per_prompt=1,\n",
+    "    ip_adapter_negative_image=negative_ip_image,\n",
+    ")\n",
+    "\n",
+    "\n",
+    "prompt = \"cinematic photo of a cyborg in the city, 4k, high quality, intricate, highly detailed\"\n",
+    "negative_prompt = \"blurry, smooth, plastic\"\n",
+    "\n",
+    "image = pipeline(\n",
+    "    prompt=prompt,\n",
+    "    negative_prompt=negative_prompt,\n",
+    "    ip_adapter_image_embeds=image_embeds,\n",
+    "    guidance_scale=6.0,\n",
+    "    num_inference_steps=25,\n",
+    "    generator=torch.Generator(device=\"cpu\").manual_seed(1556265306),\n",
+    ").images[0]\n",
+    "\n",
+    "image.save(\"result.png\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/diffusers/prompt_scheduling_callback.ipynb b/diffusers/prompt_scheduling_callback.ipynb
new file mode 100644
index 00000000..4e8b9049
--- /dev/null
+++ b/diffusers/prompt_scheduling_callback.ipynb
@@ -0,0 +1,272 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Prompt scheduling callback\n",
+    "\n",
+    "Prompt scheduling callback allows changing prompts during a generation, like [prompt editing in A1111](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#prompt-editing).\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: diffusers in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (0.31.0)\n",
+      "Requirement already satisfied: torch in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (2.2.1+cu121)\n",
+      "Requirement already satisfied: accelerate in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (1.1.1)\n",
+      "Requirement already satisfied: transformers in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (4.46.2)\n",
+      "Requirement already satisfied: importlib-metadata in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (8.5.0)\n",
+      "Requirement already satisfied: filelock in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (3.16.1)\n",
+      "Requirement already satisfied: huggingface-hub>=0.23.2 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (0.26.2)\n",
+      "Requirement already satisfied: numpy in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (1.26.4)\n",
+      "Requirement already satisfied: regex!=2019.12.17 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (2024.11.6)\n",
+      "Requirement already satisfied: requests in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (2.32.3)\n",
+      "Requirement already satisfied: safetensors>=0.3.1 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (0.4.5)\n",
+      "Requirement already satisfied: Pillow in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from diffusers) (11.0.0)\n",
+      "Requirement already satisfied: typing-extensions>=4.8.0 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (4.12.2)\n",
+      "Requirement already satisfied: sympy in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (1.13.3)\n",
+      "Requirement already satisfied: networkx in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (3.4.2)\n",
+      "Requirement already satisfied: jinja2 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (3.1.4)\n",
+      "Requirement already satisfied: fsspec in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (2024.10.0)\n",
+      "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.1.105 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (12.1.105)\n",
+      "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.1.105 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (12.1.105)\n",
+      "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.1.105 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (12.1.105)\n",
+      "Requirement already satisfied: nvidia-cudnn-cu12==8.9.2.26 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (8.9.2.26)\n",
+      "Requirement already satisfied: nvidia-cublas-cu12==12.1.3.1 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (12.1.3.1)\n",
+      "Requirement already satisfied: nvidia-cufft-cu12==11.0.2.54 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (11.0.2.54)\n",
+      "Requirement already satisfied: nvidia-curand-cu12==10.3.2.106 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (10.3.2.106)\n",
+      "Requirement already satisfied: nvidia-cusolver-cu12==11.4.5.107 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (11.4.5.107)\n",
+      "Requirement already satisfied: nvidia-cusparse-cu12==12.1.0.106 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (12.1.0.106)\n",
+      "Requirement already satisfied: nvidia-nccl-cu12==2.19.3 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (2.19.3)\n",
+      "Requirement already satisfied: nvidia-nvtx-cu12==12.1.105 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (12.1.105)\n",
+      "Requirement already satisfied: triton==2.2.0 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from torch) (2.2.0)\n",
+      "Requirement already satisfied: nvidia-nvjitlink-cu12 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from nvidia-cusolver-cu12==11.4.5.107->torch) (12.6.77)\n",
+      "Requirement already satisfied: packaging>=20.0 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from accelerate) (24.1)\n",
+      "Requirement already satisfied: psutil in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from accelerate) (6.1.0)\n",
+      "Requirement already satisfied: pyyaml in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from accelerate) (6.0.2)\n",
+      "Requirement already satisfied: tokenizers<0.21,>=0.20 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from transformers) (0.20.3)\n",
+      "Requirement already satisfied: tqdm>=4.27 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from transformers) (4.66.6)\n",
+      "Requirement already satisfied: zipp>=3.20 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from importlib-metadata->diffusers) (3.21.0)\n",
+      "Requirement already satisfied: MarkupSafe>=2.0 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from jinja2->torch) (3.0.2)\n",
+      "Requirement already satisfied: charset-normalizer<4,>=2 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from requests->diffusers) (3.4.0)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from requests->diffusers) (3.10)\n",
+      "Requirement already satisfied: urllib3<3,>=1.21.1 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from requests->diffusers) (2.2.3)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from requests->diffusers) (2024.8.30)\n",
+      "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from sympy->torch) (1.3.0)\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip install diffusers torch accelerate transformers"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "7b276fdac7b14d1cb493944859cf0334",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Fetching 15 files:   0%|          | 0/15 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8b3c586a8d5746bcb28272273b69b8cc",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "diffusion_pytorch_model.fp16.safetensors:   0%|          | 0.00/1.72G [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d4971b6b226341f2a7d9d20fb3bb9f21",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "model.fp16.safetensors:   0%|          | 0.00/246M [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "83a7bf67702d4398b7a3b6ec11622849",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "model.fp16.safetensors:   0%|          | 0.00/608M [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0ce891240d334a2a84233a1f2221757d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "diffusion_pytorch_model.fp16.safetensors:   0%|          | 0.00/167M [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "53a731ca1f1a4262acf999500ea81150",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Loading pipeline components...:   0%|          | 0/7 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from diffusers import StableDiffusionPipeline\n",
+    "from diffusers.callbacks import PipelineCallback, MultiPipelineCallbacks\n",
+    "from diffusers.configuration_utils import register_to_config\n",
+    "import torch\n",
+    "from typing import Any, Dict, Optional\n",
+    "\n",
+    "\n",
+    "pipeline: StableDiffusionPipeline = StableDiffusionPipeline.from_pretrained(\n",
+    "    \"stable-diffusion-v1-5/stable-diffusion-v1-5\",\n",
+    "    torch_dtype=torch.float16,\n",
+    "    variant=\"fp16\",\n",
+    "    use_safetensors=True,\n",
+    ").to(\"cuda\")\n",
+    "pipeline.safety_checker = None\n",
+    "pipeline.requires_safety_checker = False\n",
+    "\n",
+    "\n",
+    "class SDPromptScheduleCallback(PipelineCallback):\n",
+    "    @register_to_config\n",
+    "    def __init__(\n",
+    "        self,\n",
+    "        prompt: str,\n",
+    "        negative_prompt: Optional[str] = None,\n",
+    "        num_images_per_prompt: int = 1,\n",
+    "        cutoff_step_ratio=1.0,\n",
+    "        cutoff_step_index=None,\n",
+    "    ):\n",
+    "        super().__init__(\n",
+    "            cutoff_step_ratio=cutoff_step_ratio, cutoff_step_index=cutoff_step_index\n",
+    "        )\n",
+    "\n",
+    "    tensor_inputs = [\"prompt_embeds\"]\n",
+    "\n",
+    "    def callback_fn(\n",
+    "        self, pipeline, step_index, timestep, callback_kwargs\n",
+    "    ) -> Dict[str, Any]:\n",
+    "        cutoff_step_ratio = self.config.cutoff_step_ratio\n",
+    "        cutoff_step_index = self.config.cutoff_step_index\n",
+    "\n",
+    "        # Use cutoff_step_index if it's not None, otherwise use cutoff_step_ratio\n",
+    "        cutoff_step = (\n",
+    "            cutoff_step_index\n",
+    "            if cutoff_step_index is not None\n",
+    "            else int(pipeline.num_timesteps * cutoff_step_ratio)\n",
+    "        )\n",
+    "\n",
+    "        if step_index == cutoff_step:\n",
+    "            prompt_embeds, negative_prompt_embeds = pipeline.encode_prompt(\n",
+    "                prompt=self.config.prompt,\n",
+    "                negative_prompt=self.config.negative_prompt,\n",
+    "                device=pipeline._execution_device,\n",
+    "                num_images_per_prompt=self.config.num_images_per_prompt,\n",
+    "                do_classifier_free_guidance=pipeline.do_classifier_free_guidance,\n",
+    "            )\n",
+    "            if pipeline.do_classifier_free_guidance:\n",
+    "                prompt_embeds = torch.cat([negative_prompt_embeds, prompt_embeds])\n",
+    "            callback_kwargs[self.tensor_inputs[0]] = prompt_embeds\n",
+    "        return callback_kwargs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "bd75ef9ee32b454298a9bee7a1210627",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/50 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "callback = MultiPipelineCallbacks(\n",
+    "    [\n",
+    "        SDPromptScheduleCallback(\n",
+    "            prompt=\"Official portrait of a smiling world war ii general, female, cheerful, happy, detailed face, 20th century, highly detailed, cinematic lighting, digital art painting by Greg Rutkowski\",\n",
+    "            negative_prompt=\"Deformed, ugly, bad anatomy\",\n",
+    "            cutoff_step_ratio=0.25,\n",
+    "        )\n",
+    "    ]\n",
+    ")\n",
+    "\n",
+    "image = pipeline(\n",
+    "    prompt=\"Official portrait of a smiling world war ii general, male, cheerful, happy, detailed face, 20th century, highly detailed, cinematic lighting, digital art painting by Greg Rutkowski\",\n",
+    "    negative_prompt=\"Deformed, ugly, bad anatomy\",\n",
+    "    callback_on_step_end=callback,\n",
+    "    callback_on_step_end_tensor_inputs=[\"prompt_embeds\"],\n",
+    ").images[0]\n",
+    "\n",
+    "torch.cuda.empty_cache()\n",
+    "image.save('image2.png')"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}