init upload, on 2025-08-14 01:57:55 台北標準時間

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README_no_gallery.md

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+# HDM-xut-340M-Anime
+***World's smallest, cheapest anime-style T2I base***
+
+![](images/thumbnail.webp)
+
+## Introduction
+
+
+## Gallery
+
+{gallery}
+
+## Quick Start
+***Read [Usage Hint] section after install the model***
+
+***READ IT***
+***READ IT***
+***READ IT***
+* Use official gradio ui: https://github.com/KohakuBlueleaf/HDM
+    * Follow the readme in this repository
+* Use comfyui loader node: https://github.com/KohakuBlueleaf/HDM-ext
+    * Install this repository as comfyui custom node
+    * Use the HDM-loader node with provided safetensors file
+* Use diffusers pipeline:
+    1. Install hdm library from [github repo](https://github.com/KohakuBlueleaf/HDM)
+        ```bash
+        git clone https://github.com/KohakuBlueleaf/HDM
+        cd HDM
+        # fused: xformers fused swiglu/attention
+        # liger: liger-kernel fused swiglu
+        # tipo : tipo prompt gen system for official UI
+        # win  : windows specific (all windows user should add this)
+        # finetune: install lycoris-lora for finetune with lycoris
+        pip install -e .[tipo]
+        ## For windows user: pip install -e .[win,tipo]
+        ```
+    2. Than use pipeline from hdm
+        ```python
+        import torch
+        from hdm.pipeline import HDMXUTPipeline
+
+        torch.set_float32_matmul_precision("high")
+        pipeline = (
+            HDMXUTPipeline.from_pretrained(
+                "KBlueLeaf/HDM-xut-340M-anime",
+                trust_remote_code=True
+            )
+            .to("cuda")
+            .to(torch.float16)
+        )
+        images = pipeline("1girl....", "").images
+        ```
+
+
+## Usage Hint
+* Prompting:
+    * Use Danbooru tag + Natural Language Description
+    * For "tags", use "danbooru tag" ONLY.
+    * For tags, use comma seperated tag sequence, "without underscore"
+        * "1girl long_hair" -> "1girl, long hair"
+    * Make prompt as detail as possible
+        * TIPO is highly recommended to use here!!!
+* Sampling settings:
+    * CFG scale: 2~4
+    * Inference steps: at least 8, works best in 16~32
+* For 1024px model, recommend following resolution (WxH):
+    * 1024xK where K >= 1024
+    * WxH where W > H, W\*H >= 1024\*1024, H <= 1024
+    * For example: 1024x1536(1:2), 1440x800(16:9), 1472x736(2:1), 1280x960(4:3)
+* Don't know where to start? New to danbooru-tag style prompting?
+    * Check danbooru.donmai.us, find any image you feel good, copy its tag!
+    * Remember to apply the transformation mentioned above.
+
+### Example prompt format
+```
+1girl, 
+izuna (blue archive), blue archive, 
+
+fukamiki kei, tail, halo, skin fang, solo, eyeshadow, medium breasts, short hair, skirt, makeup, hair ornament, pink halo, yellow eyes, fox tail, scarf, pom pom hair ornament, fox girl, river, pleated skirt, leaning forward, animal ears, fang, black hair, black skirt, one side up, nature, pink scarf, sleeveless, miniskirt, open mouth, looking at viewer, fox hair ornament, breasts, animal ear fluff, fox ears, outdoors, wading, pink eyeshadow, forest, pom pom (clothes), smile, waterfall, sunlight, white shirt, sleeveless shirt, sailor collar, shirt, tail raised, partially submerged, blush, water, cowboy shot, blue sailor collar, :d,
+
+This image is a digital illustration by the artist masabodo, known for their detailed and vibrant style. The central character in the artwork is Izuna from the series "Blue Archive," depicted with fox-like features including pointed ears and a fluffy tail. Izuna is portrayed with her characteristic black hair adorned with pink ribbons, wearing a sailor-style outfit that includes a blue collar and skirt. The overall scene exudes a sense of tranquility and grace, capturing a moment of serene beauty in nature.
+
+masterpiece, newest, absurdres
+```
+
+Or with placeholder:
+```
+<|special|>, 
+<|characters|>, <|series|>, 
+<|artist|>, 
+
+<|general content tags|>,
+
+<|natural language|>.
+
+<|quality|>, <|rating|>, <|meta|>
+```
+
+***NOTE***: In ComfyUI, you ***SHOULD*** use backslash for ALL the bracket. for example `izuna (blue archive)` -> `izuna \(blue archive\)`. To ensure TIPO to works correctly and the bracket will be sent to the model.
+
+## Model Spec
+***HDM-XUT overview***
+![](images/HDM-overview.png)
+
+***XUT arch details***
+![](images/XUT-arch.png)
+
+### Model Setup
+* 343M XUT diffusion
+* 596M Qwen3 Text Encoder (qwen3-0.6B)
+* [EQ-SDXL-VAE](https://huggingface.co/KBlueLeaf/EQ-SDXL-VAE)
+* Support 1024x1024 or higher resolution
+    * 512px/768px checkpoints provided
+* Sampling method/Training Objective: Flow Matching
+* Inference Steps: 16~32
+* Hardware Recommendations: any Nvidia GPU with tensor core and >=6GB vram
+* Minimal Requirements: x86-64 computer with more than 16GB ram
+    * 512 and 768px can achieve reasonable speed on CPU
+
+
+### Dataset
+* [Danbooru2023](https://huggingface.co/datasets/KBlueLeaf/danbooru2023-webp-4Mpixel) (around 7.6M images, latest id around 8.2M)
+* Curated [Pixiv set](https://huggingface.co/datasets/Amber-River/Pixiv-2.6M) (around 700k images)
+* Private pvc figure photos.
+
+### Training
+
+| Stage | 256² | 512² | 768² | 1024² |
+|---|---|---|---|---|
+| Dataset | Danbooru 2023 | Danbooru2023 + extra* | - | curated** |
+| Image Count | 7.624M | 8.469M | - | 3.649M |
+| Epochs | 20 | 5 | 1 | 1 |
+| Samples Seen | 152.5M | 42.34M | 8.469M | 3.649M |
+| Patches Seen | 39B | 43.5B | 19.5B | 15B |
+| Learning Rate (muP, base_dim=1) | 0.5 | 0.1 | 0.05 | 0.02 |
+| Batch Size (per GPU) | 128 | 64 | 64 | 16 |
+| Gradient Checkpointing | No | Yes | Yes | Yes |
+| Gradient Accumulation | 4 | 2 | 2 | 4 |
+| Global Batch Size | 2048 | 512 | 512 | 256 |
+| TREAD Selection Rate | 0.5 | 0.5 | 0.5 | 0.0 |
+| Context Length | 256 | 256 | 256 | 512 |
+| Training Wall Time | 174h | 120h | 42h | 49h |
+
+## Limitations
+* Due to constrained training budget and model size:
+    * This model require user to provide highly detailed and well structured prompt to works well.
+        * Users are highly recommended to use TIPO
+    * This model are not good at generate good detail structure or not well-annotated concept (such as hands or special ornaments)
+* This model can only generate anime-style images for now due to dataset choice.
+    * A more general T2I model is under training, stay tuned.

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