AnimeBoysZeroXL
Creating models is a labor of love, but it takes a significant amount of time and compute power to get them just right. If youβre enjoying my models, consider fueling my next project with a coffee on Ko-fi β. Thank you for keeping this project going!

- Prompt
- score_9, 2boys, male focus, multiple boys, yaoi, couple, princess carry, carrying, collared shirt, shirt, pants, jacket, looking at another, smile, wedding, absurdres, highres, year 2025
- Negative Prompt
- score_1, score_2, score_3, lowres, artistic error, film grain, scan artifacts, jpeg artifacts, chromatic aberration, dithering, halftone, screentones, multiple views, logo, too many watermarks, negative space, blank page

- Prompt
- score_9, A handsome anime boy playing acoustic guitar in living room at home, absurdres, highres
- Negative Prompt
- score_1, score_2, score_3, lowres, artistic error, film grain, scan artifacts, jpeg artifacts, chromatic aberration, dithering, halftone, screentones, multiple views, logo, too many watermarks, negative space, blank page

- Prompt
- score_9, tachibana makoto, free!, 1boy, male focus, solo, lying, on bed, bed, pillow, bedroom, shirt, pants, looking at viewer, one eye closed, sleepy, open mouth, absurdres, highres, year 2025
- Negative Prompt
- score_1, score_2, score_3, lowres, artistic error, film grain, scan artifacts, jpeg artifacts, chromatic aberration, dithering, halftone, screentones, multiple views, logo, too many watermarks, negative space, blank page

- Prompt
- score_9, 2boys, male focus, multiple boys, rating:general, arm around shoulder, tank top, shorts, bara, muscular male, muscular, baseball cap, hat, looking at viewer, absurdres, highres, year 2025
- Negative Prompt
- score_1, score_2, score_3, lowres, artistic error, film grain, scan artifacts, jpeg artifacts, chromatic aberration, dithering, halftone, screentones, multiple views, logo, too many watermarks, negative space, blank page
A dedicated model for high-quality anime-style male characters. This model is specifically optimized for males-only content, offering a wide range of aesthetic styles and high versatility.
π Inference Guide
- β οΈ Important: This model uses Zero Terminal SNR with V-prediction. Please ensure you are using the correct settings during inference.
- ComfyUI Users: Add the
ModelSamplingDiscretenode into your workflow. Setsamplingtov_prediction,zsnrtotrue. - Automatic1111 Users: Place the
.yamlconfig file into the model folder. The .yaml file must have the exact same name as the model file, only with the.yamlextension instead of.safetensors. SetNoise schedule for samplingin settings toZero Terminal SNR.
- ComfyUI Users: Add the
- Prompting: Always begin your prompt with a score tag (e.g.
score_9). You can use any of these styles:- Tag soup:
score_X, tag1, tag2, tag3, ... - Natural language:
score_X, [your description here] - Mixed approach:
score_X, [description], tag1, tag2, ... - Tip: If you find the style of the score tags is too strong, you could try dropping them from the prompt.
- Tag soup:
- Negative Prompt: Choose from one of these three presets depending on your needs:
- Minimal:
score_1 - Light:
score_1, lowres, artistic error, scan artifacts, jpeg artifacts, multiple views, too many watermarks, negative space, blank page - Heavy:
score_1, score_2, score_3, lowres, artistic error, film grain, scan artifacts, jpeg artifacts, chromatic aberration, dithering, halftone, screentones, multiple views, logo, too many watermarks, negative space, blank page
- Minimal:
- CFG Scale: A CFG scale of 3 to 5 is recommended. For finer control, I suggest using dynamic thresholding.
- Pro-tip: I set
mimic_scaleto match the CFG scale and set both minimum scales to the same lower value. I useHalf Cosine Upfor both modes.
- Pro-tip: I set
- Resolution: To get started, try these dimensions:
- Portrait: 832 Γ 1216
- Square: 1024 Γ 1024
- Landscape: 1216 Γ 832
- Some other supported sizes: 768Γ1344, 768Γ1280, 896Γ1152, 960Γ1088, 1344Γ768, 1280Γ768, 1152Γ896, 1088Γ960.
𧨠Diffusers Example Usage
import torch
from diffusers import DiffusionPipeline
pipe = DiffusionPipeline.from_pretrained(
"Koolchh/AnimeBoysZeroXL",
torch_dtype=torch.float16,
use_safetensors=True,
variant="fp16"
)
pipe.to("cuda")
prompt = "score_9, 1boy, male focus, shirt, solo, looking at viewer, smile, black hair, brown eyes, short hair"
negative_prompt = "score_1"
image = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
width=1024,
height=1024,
guidance_scale=5,
num_inference_steps=28
).images[0]
π§ͺ Training Details
AnimeBoysZeroXL was fine-tuned from Pony Diffusion V6 XL using approximately 950k images. The knowledge cutoff is November 2025.
The following tags were used during training to help you steer the results toward your desired style.
Score tags
- Each image is tagged with
score_X, whereXis a range from 1 to 9.score_9represents the highest aesthetic quality based on my personal preferences.
Rating tags
| tag | rating |
|---|---|
rating:general |
general |
rating:sensitive |
sensitive |
rating:questionable |
questionable |
rating:explicit |
explicit |
Year tags
Use year YYYY (ranging from 2005 to 2025) to target specific era styles.
Training configurations
- Hardware: 4 Γ Nvidia A100 SXM 80GB
- Optimizer: AdaFactor
- Gradient Accumulation Steps: 8
- Effective Batch Size: 128 (4 Γ 8 Γ 4)
- Learning Rates:
- U-Net: 2e-5
- Text Encoders: 1e-5
- LR Schedule: Constant with 250 warmup steps
- Precision: FP16 Mixed Precision
π Changes from AnimeBoysXL v3.0
- Tag Overhaul: Quality tags have been removed. The 5-category aesthetic tags have been replaced with a more granular 9-category score tag system. Renamed rating tags for better clarity. Abolished the tag ordering scheme.
- Captions: A subset of highly aesthetic images was trained using natural language prompts for better comprehension.
- Emphasis: Highly aesthetic images now have more "repeats" in the training data.
- Optimization:
- 5% caption dropout for unconditional guidance.
- Trained with Zero Terminal SNR and V-prediction.
- Implemented adaptive loss weighting.
- No multi-resolution noise or debiased estimation loss.
- Trained with input perturbation noise (gamma=0.1).
- Trained with huber loss.
- Merging: This model is a merge across several iterations of the same training run for better stability.
License
AnimeBoysZeroXL is a derivative model of Pony Diffusion V6 XL by PurpleSmartAI. Please read their license before using the model.
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