mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-08-08 23:10:15 -03:00
97b9b1f62b
- Three-state autov3 field (not-checked / checked-unavailable / 12-hex value) in .metadata.json sidecars, in-memory ModelHashIndex, and SQLite (models.autov3 column + autov3_index table) with column-presence migration - Background self-terminating backfill for legacy rows: per-model-type concurrency guard, executor-offloaded I/O, Civitai-first resolution (SHA256-matched version file) falling back to the embedded safetensors header hash - Civitai-first propagation on metadata refresh, scan, and download paths; reject the empty-string SHA256 placeholder and strip OneTrainer 0x prefix - List API hash filters and hash index lookups accept 12-char AutoV3 - Cap safetensors header reads at 64 MiB to prevent crafted-file allocation - Prevent stale AutoV3 mappings on file replacement while preserving them on same-file re-registration (lazy-hash completion)
259 lines
6.3 KiB
Python
259 lines
6.3 KiB
Python
NSFW_LEVELS = {
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"PG": 1,
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"PG13": 2,
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"R": 4,
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"X": 8,
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"XXX": 16,
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"Blocked": 32, # Probably not actually visible through the API without being logged in on model owner account?
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}
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# Node type constants
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NODE_TYPES = {
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"Lora Loader (LoraManager)": 1,
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"Lora Stacker (LoraManager)": 2,
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"WanVideo Lora Select (LoraManager)": 3,
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"Create Hook LoRA (LoraManager)": 4,
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}
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# Default ComfyUI node color when bgcolor is null
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DEFAULT_NODE_COLOR = "#353535"
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# preview extensions
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PREVIEW_EXTENSIONS = [
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".webp",
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".preview.webp",
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".preview.png",
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".preview.jpeg",
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".preview.jpg",
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".preview.mp4",
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".png",
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".jpeg",
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".jpg",
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".mp4",
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".gif",
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".webm",
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".avif",
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".jxl",
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]
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# Card preview image width
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CARD_PREVIEW_WIDTH = 480
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# Width for optimized example images
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EXAMPLE_IMAGE_WIDTH = 832
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# Supported media extensions for example downloads
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SUPPORTED_MEDIA_EXTENSIONS = {
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"images": [".jpg", ".jpeg", ".png", ".webp", ".gif", ".avif", ".jxl"],
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"videos": [".mp4", ".webm"],
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}
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# Model weight file extensions recognised by scanners.
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# This is the union of all scanner extensions (lora, checkpoint, embedding).
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MODEL_FILE_EXTENSIONS = {
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".safetensors",
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".ckpt",
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".pt",
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".pt2",
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".bin",
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".pth",
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".pkl",
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".sft",
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".gguf",
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}
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# Valid sub-types for each scanner type
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VALID_LORA_SUB_TYPES = ["lora", "locon", "dora"]
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VALID_CHECKPOINT_SUB_TYPES = ["checkpoint", "diffusion_model"]
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VALID_EMBEDDING_SUB_TYPES = ["embedding"]
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# Backward compatibility alias
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VALID_LORA_TYPES = VALID_LORA_SUB_TYPES
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# Supported Civitai model types for user model queries (case-insensitive)
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CIVITAI_USER_MODEL_TYPES = [
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*VALID_LORA_TYPES,
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"textualinversion",
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"checkpoint",
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]
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# Default chunk size in megabytes used for hashing large files.
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DEFAULT_HASH_CHUNK_SIZE_MB = 4
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# Upper bound for a safetensors header block (bytes). Real headers are at most
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# a few MB (tensor name/shape lists); the cap prevents a crafted file with an
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# absurd 64-bit header length from forcing a multi-GB allocation during scan.
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MAX_SAFETENSORS_HEADER_BYTES = 64 * 1024 * 1024
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# First 12 chars of the SHA256 of an empty byte string. Some (re-packaging)
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# training tools write this placeholder into safetensors metadata instead of a
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# real hash; it must never be treated as a valid AutoV3 — several broken
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# models sharing it would collide in the hash index and falsely match recipes.
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INVALID_AUTOV3_EMPTY_HASH = "e3b0c44298fc"
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# Auto-organize settings
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AUTO_ORGANIZE_BATCH_SIZE = (
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50 # Process models in batches to avoid overwhelming the system
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)
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# Civitai model tags in priority order for subfolder organization
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CIVITAI_MODEL_TAGS = [
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"character",
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"concept",
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"clothing",
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"realistic",
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"anime",
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"toon",
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"furry",
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"style",
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"poses",
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"background",
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"tool",
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"vehicle",
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"buildings",
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"objects",
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"assets",
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"animal",
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"action",
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]
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# Default priority tag configuration strings for each model type
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DEFAULT_PRIORITY_TAG_CONFIG = {
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"lora": ", ".join(CIVITAI_MODEL_TAGS),
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"checkpoint": ", ".join(CIVITAI_MODEL_TAGS),
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"embedding": ", ".join(CIVITAI_MODEL_TAGS),
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}
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# baseModel values from CivitAI that should be treated as diffusion models (unet)
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# These model types are incorrectly labeled as "checkpoint" by CivitAI but are actually diffusion models
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DIFFUSION_MODEL_BASE_MODELS = frozenset(
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[
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"Anima",
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# Flux series — DiT architecture, loaded via UNETLoader in ComfyUI
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"Flux.1 D",
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"Flux.1 S",
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"Flux.1 Krea",
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"Flux.1 Kontext",
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"Flux.2 D",
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"Flux.2 Klein 9B",
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"Flux.2 Klein 9B-base",
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"Flux.2 Klein 4B",
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"Flux.2 Klein 4B-base",
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# Non-UNet / DiT image diffusion models
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"AuraFlow",
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"Chroma",
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"HiDream",
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"Hunyuan 1",
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"Kolors",
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"Lumina",
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"PixArt a",
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"PixArt E",
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# Video diffusion models
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"CogVideoX",
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"Hunyuan Video",
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"LTXV",
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"LTXV2",
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"LTXV 2.3",
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"Mochi",
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"SVD",
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"Wan Video",
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"Wan Video 1.3B t2v",
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"Wan Video 14B t2v",
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"Wan Video 14B i2v 480p",
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"Wan Video 14B i2v 720p",
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"Wan Video 2.2 TI2V-5B",
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"Wan Video 2.2 I2V-A14B",
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"Wan Video 2.2 T2V-A14B",
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"Wan Video 2.5 T2V",
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"Wan Video 2.5 I2V",
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# Other diffusion models
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"Ernie",
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"Ernie Turbo",
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"Nucleus",
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"Qwen",
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"ZImageBase",
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"ZImageTurbo",
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# Krea 2 — loaded via UNETLoader in ComfyUI
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"Krea 2",
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]
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)
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# Supported baseModel values for download exclusion settings.
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# Keep this aligned with static/js/utils/constants.js, excluding the generic "Other" value.
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SUPPORTED_DOWNLOAD_SKIP_BASE_MODELS = frozenset(
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[
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"SD 1.4",
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"SD 1.5",
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"SD 1.5 LCM",
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"SD 1.5 Hyper",
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"SD 2.0",
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"SD 2.1",
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"SD 3",
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"SD 3.5",
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"SD 3.5 Medium",
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"SD 3.5 Large",
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"SD 3.5 Large Turbo",
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"SDXL 1.0",
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"SDXL Lightning",
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"SDXL Hyper",
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"Flux.1 D",
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"Flux.1 S",
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"Flux.1 Krea",
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"Flux.1 Kontext",
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"Flux.2 D",
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"Flux.2 Klein 9B",
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"Flux.2 Klein 9B-base",
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"Flux.2 Klein 4B",
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"Flux.2 Klein 4B-base",
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"AuraFlow",
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"Chroma",
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"PixArt a",
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"PixArt E",
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"Hunyuan 1",
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"Lumina",
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"Kolors",
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"NoobAI",
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"Illustrious",
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"Pony",
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"Pony V7",
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"HiDream",
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"Qwen",
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"ZImageTurbo",
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"ZImageBase",
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"SVD",
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"LTXV",
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"LTXV2",
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"LTXV 2.3",
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"CogVideoX",
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"Mochi",
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"Wan Video",
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"Wan Video 1.3B t2v",
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"Wan Video 14B t2v",
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"Wan Video 14B i2v 480p",
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"Wan Video 14B i2v 720p",
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"Wan Video 2.2 TI2V-5B",
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"Wan Video 2.2 T2V-A14B",
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"Wan Video 2.2 I2V-A14B",
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"Wan Video 2.5 T2V",
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"Wan Video 2.5 I2V",
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"Hunyuan Video",
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"Anima",
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"ACE Audio",
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"Boogu",
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"Ernie",
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"Ernie Turbo",
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"Grok",
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"HappyHorse",
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"HiDream-O1",
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"Ideogram 4.0",
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"Krea 2",
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"Lens",
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"MAI",
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"Nucleus",
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"Qwen 2",
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"Upscaler",
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"Wan Image 2.7",
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"Wan Video 2.7",
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]
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)
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