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<h1 align="center"><img src="https://i.imgur.com/HsWXQTW.png" width="24px" alt="logo" /> Hotshot-XL</h1> |
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<h1 align="center"> |
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<a href="https://www.hotshot.co">🌐 Try it</a> |
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<a href="https://huggingface.co/hotshotco/Hotshot-XL">🃏 Model card</a> |
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<a href="https://discord.gg/85pqA3GG">💬 Discord</a> |
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</h1> |
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<p align="center"> |
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<img src="https://dvfx9cgvtgnyd.cloudfront.net/hotshot/image-gen/gif_e8a50e1e-0b2e-4ebc-8229-817703585405.gif" alt="a barbie doll smiling in kitchen, oven on fire, disaster, pink wes anderson vibes, cinematic" width="195px" height="111.42px"/> |
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<img src="https://dvfx9cgvtgnyd.cloudfront.net/hotshot/image-gen/gif_f6ca56a3-30b8-4b2a-9342-111353e85b96.gif" alt="a teddy bear writing a letter" width="195px" height="111.42px"/> |
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<img src="https://dvfx9cgvtgnyd.cloudfront.net/hotshot/image-gen/gif_6c219102-7f72-45e9-b4fa-b7a07c004ae1.gif" alt="dslr photo of mark zuckerberg happy, pulling on threads, lots of threads everywhere, laughing, hd, 8k" width="195px" height="111.42px"/> |
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<img src="https://dvfx9cgvtgnyd.cloudfront.net/hotshot/image-gen/gif_2dd3c30f-42c5-4f37-8fa6-b2494fcac4b4.gif" alt="a cat laughing" width="195px" height="111.42px"/> |
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</p> |
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Hotshot-XL is an AI text-to-GIF model trained to work alongside [Stable Diffusion XL](https://stability.ai/stable-diffusion). |
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Hotshot-XL can generate GIFs with any fine-tuned SDXL model. This means two things: |
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1. You’ll be able to make GIFs with any existing or newly fine-tuned SDXL model you may want to use. |
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2. If you'd like to make GIFs of personalized subjects, you can load your own SDXL based LORAs, and not have to worry about fine-tuning Hotshot-XL. This is awesome because it’s usually much easier to find suitable images for training data than it is to find videos. It also hopefully fits into everyone's existing LORA usage/workflows :) See more [here](#text-to-gif-with-personalized-loras). |
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Hotshot-XL is compatible with SDXL ControlNet to make GIFs in the composition/layout you’d like. See the [ControlNet](#text-to-gif-with-controlnet) section below. |
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Hotshot-XL was trained to generate 1 second GIFs at 8 FPS. |
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Hotshot-XL was trained on various aspect ratios. For best results with the base Hotshot-XL model, we recommend using it with an SDXL model that has been fine-tuned with 512x512 images. You can find an SDXL model we fine-tuned for 512x512 resolutions [here](https://huggingface.co/hotshotco/SDXL-512). |
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# 🌐 Try It |
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Try Hotshot-XL yourself here: https://www.hotshot.co |
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Or, if you'd like to run Hotshot-XL yourself locally, continue on to the sections below. |
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If you’re running Hotshot-XL yourself, you are going to be able to have a lot more flexibility/control with the model. As a very simple example, you’ll be able to change the sampler. We’ve seen best results with Euler-A so far, but you may find interesting results with some other ones. |
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# 🔧 Setup |
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### Environment Setup |
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``` |
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pip install virtualenv --upgrade |
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virtualenv -p $(which python3) venv |
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source venv/bin/activate |
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pip install -r requirements.txt |
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``` |
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### Download the Hotshot-XL Weights |
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``` |
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# Make sure you have git-lfs installed (https://git-lfs.com) |
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git lfs install |
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git clone https://huggingface.co/hotshotco/Hotshot-XL |
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``` |
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or visit [https://huggingface.co/hotshotco/Hotshot-XL](https://huggingface.co/hotshotco/Hotshot-XL) |
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### Download our fine-tuned SDXL model (or BYOSDXL) |
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- *Note*: To maximize data and training efficiency, Hotshot-XL was trained at various aspect ratios around 512x512 resolution. For best results with the base Hotshot-XL model, we recommend using it with an SDXL model that has been fine-tuned with images around the 512x512 resolution. You can download an SDXL model we trained with images at 512x512 resolution below, or bring your own SDXL base model. |
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``` |
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# Make sure you have git-lfs installed (https://git-lfs.com) |
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git lfs install |
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git clone https://huggingface.co/hotshotco/SDXL-512 |
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``` |
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or visit [https://huggingface.co/hotshotco/SDXL-512](https://huggingface.co/hotshotco/SDXL-512) |
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# 🔮 Inference |
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### Text-to-GIF |
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``` |
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python inference.py \ |
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--prompt="a bulldog in the captains chair of a spaceship, hd, high quality" \ |
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--output="output.gif" |
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``` |
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*What to Expect:* |
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| **Prompt** | Sasquatch scuba diving | a camel smoking a cigarette | Ronald McDonald sitting at a vanity mirror putting on lipstick | drake licking his lips and staring through a window at a cupcake | |
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|-----------|----------|----------|----------|----------| |
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| **Output** | <img src="https://dvfx9cgvtgnyd.cloudfront.net/hotshot/image-gen/gif_441b7ea2-9887-4124-a52b-14c9db1d15aa.gif" /> | <img src="https://dvfx9cgvtgnyd.cloudfront.net/hotshot/image-gen/gif_7956a022-0464-4441-88b8-15a6de953335.gif"/> | <img src="https://dvfx9cgvtgnyd.cloudfront.net/hotshot/image-gen/gif_35f55a64-7ed9-498e-894e-6ec7a8026fba.gif"/> | <img src="https://dvfx9cgvtgnyd.cloudfront.net/hotshot/image-gen/gif_df5f52cb-d74d-40b5-a066-2ce567dae512.gif"/> | |
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### Text-to-GIF with personalized LORAs |
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``` |
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python inference.py \ |
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--prompt="a bulldog in the captains chair of a spaceship, hd, high quality" \ |
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--output="output.gif" \ |
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--spatial_unet_base="path/to/stabilityai/stable-diffusion-xl-base-1.0/unet" \ |
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--lora="path/to/lora" |
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``` |
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*What to Expect:* |
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*Note*: The outputs below use the DDIMScheduler. |
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| **Prompt** | sks person screaming at a capri sun | sks person kissing kermit the frog | sks person wearing a tuxedo holding up a glass of champagne, fireworks in background, hd, high quality, 4K | |
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|-----------|----------|----------|----------| |
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| **Output** | <img src="https://dvfx9cgvtgnyd.cloudfront.net/hotshot/inf-temp/79a20eae-ffeb-4d24-8d22-609fa77c292f.gif" /> | <img src="https://dvfx9cgvtgnyd.cloudfront.net/hotshot/r/aakash.gif" /> | <img src="https://dvfx9cgvtgnyd.cloudfront.net/hotshot/inf-temp/4fa34a16-2835-4a12-8c59-348caa4f3891.gif" /> | |
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### Text-to-GIF with ControlNet |
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``` |
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python inference.py \ |
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--prompt="a girl jumping up and down and pumping her fist, hd, high quality" \ |
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--output="output.gif" \ |
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--control_type="depth" \ |
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--gif="https://media1.giphy.com/media/v1.Y2lkPTc5MGI3NjExbXNneXJicG1mOHJ2dzQ2Y2JteDY1ZWlrdjNjMjl3ZWxyeWFxY2EzdyZlcD12MV9pbnRlcm5hbF9naWZfYnlfaWQmY3Q9Zw/YOTAoXBgMCmFeQQzuZ/giphy.gif" |
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``` |
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By default, Hotshot-XL will create key frames from your source gif using 8 equally spaced frames and crop the keyframes to the default aspect ratio. For finer grained control, learn how to [vary aspect ratios](#varying-aspect-ratios) and [vary frame rates/lengths](#varying-frame-rates--lengths-experimental). |
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Hotshot-XL currently supports the use of one ControlNet model at a time; supporting Multi-ControlNet would be [exciting](#-further-work). |
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*What to Expect:* |
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| **Prompt** | pixar style girl putting two thumbs up, happy, high quality, 8k, 3d, animated disney render | keanu reaves holding a sign that says "HELP", hd, high quality | a woman laughing, hd, high quality | barack obama making a rainbow with their hands, the word "MAGIC" in front of them, wearing a blue and white striped hoodie, hd, high quality | |
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|-----------|----------|----------|----------|----------| |
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| **Output** | <img src="https://dvfx9cgvtgnyd.cloudfront.net/hotshot/inf-temp/387d8b68-7289-45e3-9b21-1a9e6ad8a782.gif"/> | <img src="https://dvfx9cgvtgnyd.cloudfront.net/hotshot%2Finf-temp/047543b2-d499-4de8-8fd2-3712c3a6c446.gif"/> | <img src="https://dvfx9cgvtgnyd.cloudfront.net/hotshot/inf-temp/8f50f4d8-4b86-4df7-a643-aae3e9d8634d.gif"> | <img src="https://dvfx9cgvtgnyd.cloudfront.net/hotshot/inf-temp/c133d8b7-46ad-4469-84fd-b7f7444a47a0.gif"/> | |
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| **Control** |<img src="https://media1.giphy.com/media/3o6Zt8qDiPE2d3kayI/giphy.gif?cid=ecf05e47igskj73xpl62pv8kyk9m39brlualxcz1j68vk8ul&ep=v1_gifs_related&rid=giphy.gif&ct=g"/> | <img src="https://media2.giphy.com/media/IoXVrbzUIuvTy/giphy.gif?cid=ecf05e47ill5r35i1bhxk0tr7quqbpruqivjtuy7gcgkfmx5&ep=v1_gifs_search&rid=giphy.gif&ct=g"/> | <img src="https://media0.giphy.com/media/12msOFU8oL1eww/giphy.gif"> | <img src="https://media4.giphy.com/media/3o84U6421OOWegpQhq/giphy.gif?cid=ecf05e47eufup08cz2up9fn9bitkgltb88ez37829mxz43cc&ep=v1_gifs_related&rid=giphy.gif&ct=g"/> | |
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### Varying Aspect Ratios |
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- *Note*: The base SDXL model is trained to best create images around 1024x1024 resolution. To maximize data and training efficiency, Hotshot-XL was trained at aspect ratios around 512x512 resolution. Please see [Additional Notes](#supported-aspect-ratios) for a list of aspect ratios the base Hotshot-XL model was trained with. |
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Like SDXL, Hotshot-XL was trained at various aspect ratios with aspect ratio bucketing, and includes support for SDXL parameters like target-size and original-size. This means you can create GIFs at several different aspect ratios and resolutions, just with the base Hotshot-XL model. |
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``` |
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python inference.py \ |
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--prompt="a bulldog in the captains chair of a spaceship, hd, high quality" \ |
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--output="output.gif" \ |
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--width=<WIDTH> \ |
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--height=<HEIGHT> |
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``` |
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*What to Expect:* |
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| | 512x512 | 672x384 | 384x672 | |
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|-----------|----------|----------|----------| |
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| **a monkey playing guitar, nature footage, hd, high quality** | <img src="https://dvfx9cgvtgnyd.cloudfront.net/hotshot/inf-temp/2295c6af-c345-47a4-8afe-62e77f84141b.gif"/> | <img src="https://dvfx9cgvtgnyd.cloudfront.net/hotshot/inf-temp/909a86c5-60df-459a-b662-ce4e85706303.gif"/> | <img src="https://dvfx9cgvtgnyd.cloudfront.net/hotshot/inf-temp/8512854d-66ea-41ff-919e-6e36d6e6a541.gif"> | |
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### Varying frame rates & lengths (*Experimental*) |
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By default, Hotshot-XL is trained to generate GIFs that are 1 second long with 8FPS. If you'd like to play with generating GIFs with varying frame rates and time lengths, you can try out the parameters `video_length` and `video_duration`. |
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`video_length` sets the number of frames. The default value is 8. |
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`video_duration` sets the runtime of the output gif in milliseconds. The default value is 1000. |
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Please note that you should expect unstable/"jittery" results when modifying these parameters as the model was only trained with 1s videos @ 8fps. You'll be able to improve the stability of results for different time lengths and frame rates by [fine-tuning Hotshot-XL](#-fine-tuning). Please let us know if you do! |
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``` |
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python inference.py \ |
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--prompt="a bulldog in the captains chair of a spaceship, hd, high quality" \ |
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--output="output.gif" \ |
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--video_length=16 \ |
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--video_duration=2000 |
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``` |
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### Spatial Layers Only |
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Hotshot-XL is trained to generate GIFs alongside SDXL. If you'd like to generate just an image, you can simply set `video_length=1` in your inference call and the Hotshot-XL temporal layers will be ignored, as you'd expect. |
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``` |
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python inference.py \ |
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--prompt="a bulldog in the captains chair of a spaceship, hd, high quality" \ |
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--output="output.jpg" \ |
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--video_length=1 |
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``` |
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### Additional Notes |
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#### Supported Aspect Ratios |
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Hotshot-XL was trained at the following aspect ratios; to reliably generate GIFs outside the range of these aspect ratios, you will want to fine-tune Hotshot-XL with videos at the resolution of your desired aspect ratio. |
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| Aspect Ratio | Size | |
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|--------------|------| |
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| 0.42 |320 x 768| |
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| 0.57 |384 x 672| |
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| 0.68 |416 x 608| |
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| 1.00 |512 x 512| |
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| 1.46 |608 x 416| |
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| 1.75 |672 x 384| |
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| 2.40 |768 x 320| |
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# 💪 Fine-Tuning |
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The following section relates to fine-tuning the Hotshot-XL temporal model with additional text/video pairs. If you're trying to generate GIFs of personalized concepts/subjects, we'd recommend not fine-tuning Hotshot-XL, but instead training your own SDXL based LORAs and [just loading those](#text-to-gif-with-personalized-loras). |
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### Fine-Tuning Hotshot-XL |
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#### Dataset Preparation |
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The `fine_tune.py` script expects your samples to be structured like this: |
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``` |
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fine_tune_dataset |
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├── sample_001 |
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│ ├── 0.jpg |
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│ ├── 1.jpg |
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│ ├── 2.jpg |
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... |
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... |
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│ ├── n.jpg |
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│ └── prompt.txt |
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``` |
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Each sample directory should contain your **n key frames** and a `prompt.txt` file which contains the prompt. |
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The final checkpoint will be saved to `output_dir`. |
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We've found it useful to send validation GIFs to [Weights & Biases](www.wandb.ai) every so often. If you choose to use validation with Weights & Biases, you can set how often this runs with the `validate_every_steps` parameter. |
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``` |
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accelerate launch fine_tune.py \ |
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--output_dir="<OUTPUT_DIR>" \ |
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--data_dir="fine_tune_dataset" \ |
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--report_to="wandb" \ |
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--run_validation_at_start \ |
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--resolution=512 \ |
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--mixed_precision=fp16 \ |
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--train_batch_size=4 \ |
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--learning_rate=1.25e-05 \ |
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--lr_scheduler="constant" \ |
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--lr_warmup_steps=0 \ |
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--max_train_steps=1000 \ |
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--save_n_steps=20 \ |
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--validate_every_steps=50 \ |
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--vae_b16 \ |
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--gradient_checkpointing \ |
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--noise_offset=0.05 \ |
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--snr_gamma \ |
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--test_prompts="man sits at a table in a cafe, he greets another man with a smile and a handshakes" |
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``` |
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# 📝 Further work |
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There are lots of ways we are excited about improving Hotshot-XL. For example: |
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- [ ] Fine-Tuning Hotshot-XL at larger frame rates to create longer/higher frame-rate GIFs |
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- [ ] Fine-Tuning Hotshot-XL at larger resolutions to create higher resolution GIFs |
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- [ ] Training temporal layers for a latent upscaler to produce higher resolution GIFs |
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- [ ] Training an image conditioned "frame prediction" model for more coherent, longer GIFs |
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- [ ] Training temporal layers for a VAE to mitigate flickering/dithering in outputs |
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- [ ] Supporting Multi-ControlNet for greater control over GIF generation |
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- [ ] Training & integrating different ControlNet models for further control over GIF generation (finer facial expression control would be very cool) |
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- [ ] Moving Hotshot-XL into [AITemplate](https://github.com/facebookincubator/AITemplate) for faster inference times |
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We 💗 contributions from the open-source community! Please let us know in the issues or PRs if you're interested in working on these improvements or anything else! |
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# 🙏 Acknowledgements |
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Text-to-Video models are improving quickly and the development of Hotshot-XL has been greatly inspired by the following amazing works and teams: |
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- [SDXL](https://stability.ai/stable-diffusion) |
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- [Align Your Latents](https://research.nvidia.com/labs/toronto-ai/VideoLDM/) |
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- [Make-A-Video](https://makeavideo.studio/) |
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- [AnimateDiff](https://animatediff.github.io/) |
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- [Imagen Video](https://imagen.research.google/video/) |
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We hope that releasing this model/codebase helps the community to continue pushing these creative tools forward in an open and responsible way. |
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