model/model_registry.py

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_SD3_generation"],
    "SD3",
    "https://huggingface.co/blog/sd3",
    "SD3 is a novel Multimodal Diffusion Transformer (MMDiT) model.",
)

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.",
)

register_model_info(
    ["imagenhub_HunyuanDiT_generation"],
    "HunyuanDiT",
    "https://github.com/Tencent/HunyuanDiT",
    "HunyuanDiT is a Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding",
)

# 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_StableVideoDiffusion_text2video"],
    "StableVideoDiffusion",
    "https://fal.ai/models/fal-ai/fast-svd/text-to-video/api",
    "Stable Video Diffusion empowers individuals to transform text and image inputs into vivid scenes.",
)

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.",
)