Spaces:
Running
on
Zero
Running
on
Zero
File size: 6,995 Bytes
e368cec 94bd22c e368cec e049190 e368cec 94bd22c e368cec 94bd22c e368cec 94bd22c e368cec 94bd22c e368cec 86da3fc 94bd22c 86da3fc e368cec 94bd22c e368cec 94bd22c e368cec 623aaf3 e368cec 944dd2b e368cec 944dd2b 26dad4e 944dd2b 26dad4e 944dd2b 26dad4e 65622ab e1b7db1 c3c53e2 e1b7db1 e368cec |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 |
from collections import namedtuple
from typing import List
ModelInfo = namedtuple("ModelInfo", ["simple_name", "link", "description"])
model_info = {}
def register_model_info(
full_names: List[str], simple_name: str, link: str, description: str
):
info = ModelInfo(simple_name, link, description)
for full_name in full_names:
model_info[full_name] = info
def get_model_info(name: str) -> ModelInfo:
if name in model_info:
return model_info[name]
else:
# To fix this, please use `register_model_info` to register your model
return ModelInfo(
name, "", "Register the description at fastchat/model/model_registry.py"
)
def get_model_description_md(model_list):
model_description_md = """
| | | |
| ---- | ---- | ---- |
"""
ct = 0
visited = set()
for i, name in enumerate(model_list):
minfo = get_model_info(name)
if minfo.simple_name in visited:
continue
visited.add(minfo.simple_name)
one_model_md = f"[{minfo.simple_name}]({minfo.link}): {minfo.description}"
if ct % 3 == 0:
model_description_md += "|"
model_description_md += f" {one_model_md} |"
if ct % 3 == 2:
model_description_md += "\n"
ct += 1
return model_description_md
# regist image generation models
register_model_info(
["imagenhub_LCM_generation", "fal_LCM_text2image"],
"LCM",
"https://huggingface.co/SimianLuo/LCM_Dreamshaper_v7",
"Latent Consistency Models.",
)
register_model_info(
["fal_LCM(v1.5/XL)_text2image"],
"LCM(v1.5/XL)",
"https://fal.ai/models/fast-lcm-diffusion-turbo",
"Latent Consistency Models (v1.5/XL)",
)
register_model_info(
["imagenhub_PlayGroundV2_generation", 'playground_PlayGroundV2_generation'],
"Playground v2",
"https://huggingface.co/playgroundai/playground-v2-1024px-aesthetic",
"Playground v2 – 1024px Aesthetic Model",
)
register_model_info(
["imagenhub_PlayGroundV2.5_generation", 'playground_PlayGroundV2.5_generation'],
"Playground v2.5",
"https://huggingface.co/playgroundai/playground-v2.5-1024px-aesthetic",
"Playground v2.5 is the state-of-the-art open-source model in aesthetic quality",
)
register_model_info(
["imagenhub_OpenJourney_generation"],
"Openjourney",
"https://huggingface.co/prompthero/openjourney",
"Openjourney is an open source Stable Diffusion fine tuned model on Midjourney images, by PromptHero.",
)
register_model_info(
["imagenhub_SDXLTurbo_generation", "fal_SDXLTurbo_text2image"],
"SDXLTurbo",
"https://huggingface.co/stabilityai/sdxl-turbo",
"SDXL-Turbo is a fast generative text-to-image model.",
)
register_model_info(
["imagenhub_SDXL_generation", "fal_SDXL_text2image"],
"SDXL",
"https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0",
"SDXL is a Latent Diffusion Model that uses two fixed, pretrained text encoders.",
)
register_model_info(
["imagenhub_PixArtAlpha_generation"],
"PixArtAlpha",
"https://huggingface.co/PixArt-alpha/PixArt-XL-2-1024-MS",
"Pixart-α consists of pure transformer blocks for latent diffusion.",
)
register_model_info(
["imagenhub_PixArtSigma_generation", "fal_PixArtSigma_text2image"],
"PixArtSigma",
"https://github.com/PixArt-alpha/PixArt-sigma",
"Improved version of Pixart-α.",
)
register_model_info(
["imagenhub_SDXLLightning_generation", "fal_SDXLLightning_text2image"],
"SDXL-Lightning",
"https://huggingface.co/ByteDance/SDXL-Lightning",
"SDXL-Lightning is a lightning-fast text-to-image generation model.",
)
register_model_info(
["imagenhub_StableCascade_generation", "fal_StableCascade_text2image"],
"StableCascade",
"https://huggingface.co/stabilityai/stable-cascade",
"StableCascade is built upon the Würstchen architecture and working at a much smaller latent space.",
)
# regist image edition models
register_model_info(
["imagenhub_CycleDiffusion_edition"],
"CycleDiffusion",
"https://github.com/ChenWu98/cycle-diffusion?tab=readme-ov-file",
"A latent space for stochastic diffusion models.",
)
register_model_info(
["imagenhub_Pix2PixZero_edition"],
"Pix2PixZero",
"https://pix2pixzero.github.io/",
"A zero-shot Image-to-Image translation model.",
)
register_model_info(
["imagenhub_Prompt2prompt_edition"],
"Prompt2prompt",
"https://prompt-to-prompt.github.io/",
"Image Editing with Cross-Attention Control.",
)
register_model_info(
["imagenhub_InstructPix2Pix_edition"],
"InstructPix2Pix",
"https://www.timothybrooks.com/instruct-pix2pix",
"An instruction-based image editing model.",
)
register_model_info(
["imagenhub_MagicBrush_edition"],
"MagicBrush",
"https://osu-nlp-group.github.io/MagicBrush/",
"Manually Annotated Dataset for Instruction-Guided Image Editing.",
)
register_model_info(
["imagenhub_PNP_edition"],
"PNP",
"https://github.com/MichalGeyer/plug-and-play",
"Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation.",
)
register_model_info(
["imagenhub_InfEdit_edition"],
"InfEdit",
"https://sled-group.github.io/InfEdit/",
"Inversion-Free Image Editing with Natural Language.",
)
register_model_info(
["imagenhub_CosXLEdit_edition"],
"CosXLEdit",
"https://huggingface.co/stabilityai/cosxl",
"An instruction-based image editing model from SDXL.",
)
register_model_info(
["fal_stable-cascade_text2image"],
"StableCascade",
"https://fal.ai/models/stable-cascade/api",
"StableCascade is a generative model that can generate high-quality images from text prompts.",
)
register_model_info(
["fal_AnimateDiff_text2video"],
"AnimateDiff",
"https://fal.ai/models/fast-animatediff-t2v",
"AnimateDiff is a text-driven models that produce diverse and personalized animated images.",
)
register_model_info(
["fal_AnimateDiffTurbo_text2video"],
"AnimateDiff Turbo",
"https://fal.ai/models/fast-animatediff-t2v-turbo",
"AnimateDiff Turbo is a lightning version of AnimateDiff.",
)
register_model_info(
["videogenhub_LaVie_generation"],
"LaVie",
"https://github.com/Vchitect/LaVie",
"LaVie is a video generation model with cascaded latent diffusion models.",
)
register_model_info(
["videogenhub_VideoCrafter2_generation"],
"VideoCrafter2",
"https://ailab-cvc.github.io/videocrafter2/",
"VideoCrafter2 is a T2V model that disentangling motion from appearance.",
)
register_model_info(
["videogenhub_ModelScope_generation"],
"ModelScope",
"https://arxiv.org/abs/2308.06571",
"ModelScope is a a T2V synthesis model that evolves from a T2I synthesis model.",
)
register_model_info(
["videogenhub_OpenSora_generation"],
"OpenSora",
"https://github.com/hpcaitech/Open-Sora",
"A community-driven opensource implementation of Sora.",
)
|