mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
numerous tweaks
1. only load triton on linux machines 2. require pip >= 23.0 so that editable installs can run without setup.py 3. model files default to SD-1.5, not 2.1 4. use diffusers model of inpainting rather than ckpt 5. selected a new set of initial models based on # of likes at huggingface
This commit is contained in:
Lincoln Stein
parent
3996ee843c
commit
3810d6a4ce
@ -14,7 +14,7 @@ from tempfile import TemporaryDirectory
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from typing import Union
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SUPPORTED_PYTHON = ">=3.9.0,<3.11"
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INSTALLER_REQS = ["pip", "rich", "semver", "requests", "plumbum", "prompt-toolkit"]
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INSTALLER_REQS = ["pip>=23.0", "rich", "semver", "requests", "plumbum", "prompt-toolkit"]
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BOOTSTRAP_VENV_PREFIX = "invokeai-installer-tmp"
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OS = platform.uname().system
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@ -91,7 +91,7 @@ class Installer:
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venv_dir = self.mktemp_venv()
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pip = get_pip_from_venv(Path(venv_dir.name))
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cmd = [pip, "install", "--require-virtualenv", "--use-pep517", "--upgrade"]
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cmd = [pip, "install", "--require-virtualenv", "--use-pep517"]
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cmd.extend(self.reqs)
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try:
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@ -308,6 +308,18 @@ class InvokeAiInstance:
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Configure the InvokeAI runtime directory
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"""
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print(f'DEBUG: sys.argv = {sys.argv}')
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new_argv = [sys.argv[0]]
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for i in range(1,len(sys.argv)):
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el = sys.argv[i]
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if el in ['-r','--root']:
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new_argv.append(el)
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new_argv.append(sys.argv[i+1])
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elif el in ['-y','--yes','--yes-to-all']:
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new_argv.append(el)
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sys.argv = new_argv
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print(f'DEBUG: sys.argv = {sys.argv}')
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from messages import introduction
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introduction()
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@ -317,6 +329,9 @@ class InvokeAiInstance:
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# NOTE: currently the config script does its own arg parsing! this means the command-line switches
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# from the installer will also automatically propagate down to the config script.
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# this may change in the future with config refactoring!
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# set sys.argv to a consistent state
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configure_invokeai.main()
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def install_user_scripts(self):
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@ -1,69 +1,63 @@
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stable-diffusion-2.1-768:
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description: Stable Diffusion version 2.1 diffusers model, trained on 768x768 images (5.21 GB)
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repo_id: stabilityai/stable-diffusion-2-1
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format: diffusers
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recommended: True
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stable-diffusion-2.1-base:
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description: Stable Diffusion version 2.1 diffusers base model, trained on 512x512 images (5.21 GB)
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repo_id: stabilityai/stable-diffusion-2-1-base
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format: diffusers
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recommended: False
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stable-diffusion-1.5:
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description: Stable Diffusion version 1.5 weight file (4.27 GB)
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repo_id: runwayml/stable-diffusion-v1-5
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format: diffusers
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recommended: True
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default: True
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vae:
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repo_id: stabilityai/sd-vae-ft-mse
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stable-diffusion-1.4:
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description: The original Stable Diffusion version 1.4 weight file (4.27 GB)
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repo_id: CompVis/stable-diffusion-v1-4
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recommended: False
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format: diffusers
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vae:
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repo_id: stabilityai/sd-vae-ft-mse
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width: 512
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height: 512
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inpainting-1.5:
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description: RunwayML SD 1.5 model optimized for inpainting (ckpt version) (4.27 GB)
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repo_id: runwayml/stable-diffusion-inpainting
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config: v1-inpainting-inference.yaml
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file: sd-v1-5-inpainting.ckpt
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format: ckpt
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vae:
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repo_id: stabilityai/sd-vae-ft-mse-original
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file: vae-ft-mse-840000-ema-pruned.ckpt
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recommended: True
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width: 512
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height: 512
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waifu-diffusion-1.4:
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description: Latest waifu diffusion 1.4 (diffusers version)
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default: True
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inpainting-1.5:
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description: RunwayML SD 1.5 model optimized for inpainting (4.27 GB)
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repo_id: runwayml/stable-diffusion-inpainting
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format: diffusers
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repo_id: hakurei/waifu-diffusion
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vae:
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repo_id: stabilityai/sd-vae-ft-mse
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recommended: True
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waifu-diffusion-1.3:
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description: Stable Diffusion 1.4 fine tuned on anime-styled images (ckpt version) (4.27 GB)
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repo_id: hakurei/waifu-diffusion-v1-3
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config: v1-inference.yaml
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file: model-epoch09-float32.ckpt
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format: ckpt
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vae:
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repo_id: stabilityai/sd-vae-ft-mse-original
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file: vae-ft-mse-840000-ema-pruned.ckpt
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dreamlike-diffusion-1.0:
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description: An SD 1.5 model fine tuned on high quality art by dreamlike.art
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format: diffusers
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repo_id: dreamlike-art/dreamlike-diffusion-1.0
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vae:
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repo_id: stabilityai/sd-vae-ft-mse
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recommended: True
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dreamlike-photoreal-2.0:
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description: A photorealistic model trained on 768 pixel images based on SD 1.5 (2.13 GB)
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format: diffusers
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repo_id: dreamlike-art/dreamlike-photoreal-2.0
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recommended: False
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stable-diffusion-2.1-768:
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description: Stable Diffusion version 2.1 diffusers model, trained on 768 pixel images (5.21 GB)
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repo_id: stabilityai/stable-diffusion-2-1
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format: diffusers
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recommended: True
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stable-diffusion-2.1-base:
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description: Stable Diffusion version 2.1 diffusers base model, trained on 512 pixel images (5.21 GB)
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repo_id: stabilityai/stable-diffusion-2-1-base
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format: diffusers
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recommended: False
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width: 512
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height: 512
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openjourney-4.0:
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description: An SD 1.5 model fine tuned on Midjourney images by PromptHero - include "mdjrny-v4 style" in your prompts (2.13 GB)
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format: diffusers
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repo_id: prompthero/openjourney
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vae:
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repo_id: stabilityai/sd-vae-ft-mse
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recommended: False
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nitro-diffusion-1.0:
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description: A SD 1.5 model trained on three artstyles - prompt with "archer style", "arcane style" and/or "modern disney style" (2.13 GB)
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repo_id: nitrosocke/Nitro-Diffusion
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format: diffusers
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vae:
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repo_id: stabilityai/sd-vae-ft-mse
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recommended: False
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trinart-2.0:
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description: An SD model finetuned with ~40,000 assorted high resolution manga/anime-style pictures (2.13 GB)
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repo_id: naclbit/trinart_stable_diffusion_v2
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format: diffusers
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recommended: False
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vae:
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repo_id: stabilityai/sd-vae-ft-mse
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trinart_characters-2_0:
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recommended: False
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trinart-characters-2_0:
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description: An SD model finetuned with 19.2M anime/manga style images (ckpt version) (4.27 GB)
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repo_id: naclbit/trinart_derrida_characters_v2_stable_diffusion
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config: v1-inference.yaml
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@ -72,50 +66,24 @@ trinart_characters-2_0:
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vae:
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repo_id: naclbit/trinart_derrida_characters_v2_stable_diffusion
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file: autoencoder_fix_kl-f8-trinart_characters.ckpt
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recommended: False
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width: 512
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height: 512
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anything-4.0:
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description: High-quality, highly detailed anime style images with just a few prompts
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format: diffusers
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repo_id: andite/anything-v4.0
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vae:
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repo_id: stabilityai/sd-vae-ft-mse
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recommended: False
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papercut-1.0:
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description: SD 1.5 fine-tuned for papercut art (use "PaperCut" in your prompts) (2.13 GB)
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repo_id: Fictiverse/Stable_Diffusion_PaperCut_Model
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format: diffusers
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vae:
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repo_id: stabilityai/sd-vae-ft-mse
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recommended: False
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voxel_art-1.0:
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description: Stable Diffusion trained on voxel art (use "VoxelArt" in your prompts) (4.27 GB)
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repo_id: Fictiverse/Stable_Diffusion_VoxelArt_Model
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config: v1-inference.yaml
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file: VoxelArt_v1.ckpt
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format: ckpt
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vae:
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repo_id: stabilityai/sd-vae-ft-mse
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file: vae-ft-mse-840000-ema-pruned.ckpt
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recommended: False
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width: 512
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height: 512
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ft-mse-improved-autoencoder-840000:
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description: StabilityAI improved autoencoder fine-tuned for human faces. Use with legacy .ckpt models ONLY (335 MB)
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description: StabilityAI improved autoencoder fine-tuned for human faces. Improves legacy .ckpt models (335 MB)
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repo_id: stabilityai/sd-vae-ft-mse-original
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format: ckpt
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config: VAE/default
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file: vae-ft-mse-840000-ema-pruned.ckpt
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recommended: True
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width: 512
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height: 512
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recommended: True
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trinart_vae:
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description: Custom autoencoder for trinart_characters for legacy .ckpt models only (335 MB)
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repo_id: naclbit/trinart_characters_19.2m_stable_diffusion_v1
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config: VAE/trinart
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format: ckpt
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file: autoencoder_fix_kl-f8-trinart_characters.ckpt
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recommended: False
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width: 512
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height: 512
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recommended: False
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File diff suppressed because it is too large
Load Diff
@ -60,6 +60,7 @@ dependencies = [
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"opencv-python",
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"picklescan",
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"pillow",
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'pip>=23.0',
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"pudb",
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"prompt-toolkit",
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"pypatchmatch",
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@ -91,7 +92,7 @@ dependencies = [
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"test" = ["pytest>6.0.0", "pytest-cov"]
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"xformers" = [
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"xformers~=0.0.16; sys_platform!='darwin'",
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"triton; sys_platform!='darwin'",
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"triton; sys_platform=='linux'",
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]
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[project.scripts]
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