model/model_registry.py

from collections import namedtuple
from typing import List

ModelInfo = namedtuple("ModelInfo", ["simple_name", "link", "description", "license", "organization", "type"])
model_info = {}

def register_model_info(
    full_names: List[str], simple_name: str, link: str, description: str,
    license: str, organization: str, model_type: str
):
    info = ModelInfo(simple_name, link, description, license, organization, model_type)
    for full_name in full_names:
        model_info[full_name] = info
        model_info[full_name.split("_")[1]] = info
    model_info[simple_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",
            "-", "-", None
        )

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.",
    "MIT License",
    "Tsinghua University",
    "text2image_generation"
)

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)",
    "openrail++",
    "Latent Consistency",
    "text2image_generation"
)

register_model_info(
    ["imagenhub_PlayGroundV2_generation", 'playground_PlayGroundV2_generation'],
    "PlayGround V2",
    "https://huggingface.co/playgroundai/playground-v2-1024px-aesthetic",
    "Playground v2 – 1024px Aesthetic Model",
    "Playground v2 Community License",
    "Playground",
    "text2image_generation"
)

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",
    "Playground v2.5 Community License",
    "Playground",
    "text2image_generation"
)

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.",
    "creativeml-openrail-m",
    "PromptHero",
    "text2image_generation"
)

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.",
    "sai-nc-community (other)",
    "Stability AI",
    "text2image_generation"
)

register_model_info(
    ["imagenhub_SDEdit_edition"],
    "SDEdit",
    "https://sde-image-editing.github.io",
    "SDEdit is an image synthesis and editing framework based on stochastic differential equations (SDEs) or diffusion models.",
    "MIT License",
    "Stanford University",
    "image_edition"
)

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.",
    "openrail++",
    "Stability AI",
    "text2image_generation"
)

register_model_info(
    ["imagenhub_SD3_generation"],
    "SD3",
    "https://huggingface.co/blog/sd3",
    "SD3 is a novel Multimodal Diffusion Transformer (MMDiT) model.",
    "stabilityai-nc-research-community",
    "Stability AI",
    "text2image_generation"
)

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.",
    "openrail++",
    "PixArt-alpha",
    "text2image_generation"
)

register_model_info(
    ["imagenhub_PixArtSigma_generation", "fal_PixArtSigma_text2image"],
    "PixArtSigma",
    "https://github.com/PixArt-alpha/PixArt-sigma",
    "Improved version of Pixart-α.",
    "openrail++",
    "PixArt-alpha",
    "text2image_generation"
)

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.",
    "openrail++",
    "ByteDance",
    "text2image_generation"
)

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.",
    "stable-cascade-nc-community (other)",
    "Stability AI",
    "text2image_generation"
)

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",
    "tencent-hunyuan-community",
    "Tencent",
    "text2image_generation"
)

register_model_info(
    ["imagenhub_Kolors_generation"],
    "Kolors",
    "https://huggingface.co/Kwai-Kolors/Kolors",
    "Kolors is a large-scale text-to-image generation model based on latent diffusion",
    "Apache-2.0",
    "Kwai Kolors",
    "text2image_generation"
)

register_model_info(
    ["fal_AuraFlow_text2image"],
    "AuraFlow",
    "https://huggingface.co/fal/AuraFlow",
    "Opensourced flow-based text-to-image generation model.",
    "Apache-2.0",
    "Fal.AI",
    "text2image_generation"
)

register_model_info(
    ["fal_FLUX1schnell_text2image"],
    "FLUX.1-schnell",
    "https://huggingface.co/docs/diffusers/main/en/api/pipelines/flux",
    "Flux is a series of text-to-image generation models based on diffusion transformers. Timestep-distilled version.",
    "Apache-2.0",
    "Black Forest Labs",
    "text2image_generation"
)

register_model_info(
    ["fal_FLUX1dev_text2image"],
    "FLUX.1-dev",
    "https://huggingface.co/docs/diffusers/main/en/api/pipelines/flux",
    "Flux is a series of text-to-image generation models based on diffusion transformers. Guidance-distilled version.",
    "flux-1-dev-non-commercial-license (other)",
    "Black Forest Labs",
    "text2image_generation"
)


# 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.",
    "X11",
    "Carnegie Mellon University",
    "image_edition"
)

register_model_info(
    ["imagenhub_Pix2PixZero_edition"],
    "Pix2PixZero",
    "https://pix2pixzero.github.io/",
    "A zero-shot Image-to-Image translation model.",
    "MIT License",
    "Carnegie Mellon University, Adobe Research",
    "image_edition"
)

register_model_info(
    ["imagenhub_Prompt2prompt_edition"],
    "Prompt2prompt",
    "https://prompt-to-prompt.github.io/",
    "Image Editing with Cross-Attention Control.",
    "Apache-2.0",
    "Google, Tel Aviv University",
    "image_edition"
)


register_model_info(
    ["imagenhub_InstructPix2Pix_edition"],
    "InstructPix2Pix",
    "https://www.timothybrooks.com/instruct-pix2pix",
    "An instruction-based image editing model.",
    "Copyright 2023 Timothy Brooks, Aleksander Holynski, Alexei A. Efros",
    "University of California, Berkeley",
    "image_edition"
)

register_model_info(
    ["imagenhub_MagicBrush_edition"],
    "MagicBrush",
    "https://osu-nlp-group.github.io/MagicBrush/",
    "Manually Annotated Dataset for Instruction-Guided Image Editing.",
    "CC-BY-4.0",
    "The Ohio State University, University of Waterloo",
    "image_edition"
)

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.",
    "-",
    "Weizmann Institute of Science",
    "image_edition"
)

register_model_info(
    ["imagenhub_InfEdit_edition"],
    "InfEdit",
    "https://sled-group.github.io/InfEdit/",
    "Inversion-Free Image Editing with Natural Language.",
    "CC BY-NC-ND 4.0",
    "University of Michigan, University of California, Berkeley",
    "image_edition"
)

register_model_info(
    ["imagenhub_CosXLEdit_edition"],
    "CosXLEdit",
    "https://huggingface.co/stabilityai/cosxl",
    "An instruction-based image editing model from SDXL.",
    "cosxl-nc-community",
    "Stability AI",
    "image_edition"
)

register_model_info(
    ["imagenhub_UltraEdit_edition"],
    "UltraEdit",
    "https://ultra-editing.github.io/",
    "Instruction-based Fine-Grained Image Editing at Scale.",
    "other",
    "Peking University; BIGAI",
    "image_edition"
)

register_model_info(
    ["imagenhub_AURORA_edition"],
    "AURORA",
    "https://aurora-editing.github.io/",
    "AURORA (Action Reasoning Object Attribute) enables training an instruction-guided image editing model that can perform action and reasoning-centric edits.",
    "MIT",
    "McGill NLP",
    "image_edition"
)

register_model_info(
    ["imagenhub_FluxEdit_edition"],
    "FluxEdit",
    "https://github.com/sayakpaul/flux-image-editing",
    "Flux Control trained on OmniEdit dataset",
    "Apache 2.0",
    "HuggingFace",
    "image_edition"
)

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.",
    "stable-cascade-nc-community (other)",
    "Stability AI",
    "image_edition"
)

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.",
    "creativeml-openrail-m",
    "The Chinese University of Hong Kong, Shanghai AI Lab, Stanford University",
    "text2video_generation"
)

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.",
    "SVD-nc-community",
    "Stability AI",
    "text2video_generation"
)

register_model_info(
    ["fal_AnimateDiffTurbo_text2video"],
    "AnimateDiff Turbo",
    "https://fal.ai/models/fast-animatediff-t2v-turbo",
    "AnimateDiff Turbo is a lightning version of AnimateDiff.",
    "creativeml-openrail-m",
    "The Chinese University of Hong Kong, Shanghai AI Lab, Stanford University",
    "text2video_generation"
)

register_model_info(
    ["videogenhub_VideoCrafter2_generation"],
    "VideoCrafter2",
    "https://ailab-cvc.github.io/videocrafter2/",
    "VideoCrafter2 is a T2V model that disentangling motion from appearance.",
    "Apache 2.0",
    "Tencent AI Lab",
    "text2video_generation"
)

register_model_info(
    ["videogenhub_LaVie_generation"],
    "LaVie",
    "https://github.com/Vchitect/LaVie",
    "LaVie is a video generation model with cascaded latent diffusion models.",
    "Apache 2.0",
    "Shanghai AI Lab",
    "text2video_generation"
)
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.",
    "cc-by-nc-4.0",
    "Alibaba Group",
    "text2video_generation"
)

register_model_info(
    ["videogenhub_OpenSora_generation"],
    "OpenSora",
    "https://github.com/hpcaitech/Open-Sora",
    "A community-driven opensource implementation of Sora.",
    "Apache 2.0",
    "HPC-AI Tech",
    "text2video_generation"
)

register_model_info(
    ["videogenhub_OpenSora12_generation"],
    "OpenSora v1.2",
    "https://github.com/hpcaitech/Open-Sora",
    "A community-driven opensource implementation of Sora. v1.2",
    "Apache 2.0",
    "HPC-AI Tech",
    "text2video_generation"
)

register_model_info(
    ["videogenhub_CogVideoX-2B_generation"],
    "CogVideoX-2B",
    "https://github.com/THUDM/CogVideo",
    "Text-to-Video Diffusion Models with An Expert Transformer.",
    "CogVideoX LICENSE",
    "THUDM",
    "text2video_generation"
)

register_model_info(
    ["videogenhub_PyramidFlow_text2video"],
    "Pyramid Flow",
    "https://pyramid-flow.github.io/",
    "Pyramidal Flow Matching for Efficient Video Generative Modeling.",
    "MIT LICENSE",
    "Peking University",
    "text2video_generation"
)
register_model_info(
    ["fal_CogVideoX-5B_text2video"],
    "CogVideoX-5B",
    "https://github.com/THUDM/CogVideo",
    "Text-to-Video Diffusion Models with An Expert Transformer.",
    "CogVideoX LICENSE",
    "THUDM",
    "text2video_generation"
)
    
register_model_info(
    ["fal_T2VTurbo_text2video"],
    "T2V-Turbo",
    "https://github.com/Ji4chenLi/t2v-turbo",
    "Video Consistency Model with Mixed Reward Feedback.",
    "cc-by-nc-4.0",
    "University of California, Santa Barbara",
    "text2video_generation"
)
    
register_model_info(
    ["videogenhub_Allegro_text2video"],
    "Allegro",
    "https://github.com/rhymes-ai/Allegro",
    "DiT based Video Generation Model",
    "Apache 2.0",
    "rhymes-ai",
    "text2video_generation"
)
    
register_model_info(
    ["videogenhub_LTXVideo_text2video"],
    "LTXVideo",
    "https://github.com/Lightricks/LTX-Video",
    "DiT based Video Generation Model",
    "Apache 2.0",
    "Lightricks",
    "text2video_generation"
)
    
register_model_info(
    ["videogenhub_Mochi1_text2video"],
    "Mochi1",
    "https://github.com/genmoai/mochi",
    "Mochi 1 preview is an open state-of-the-art video generation model with high-fidelity motion and strong prompt adherence in preliminary evaluation.",
    "Apache 2.0",
    "Genmo AI",
    "text2video_generation"
)