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CHAITron/
KranokThaiV1

Name: KranokThaiV1
Availability: InStock

creativeml-openrail-m

autotrain_compatible

endpoints_compatible

StableDiffusionPipeline

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KranokThaiV1 🇹🇭

model by CHAITron

This is the fine-tuned Stable Diffusion model trained on the concept of Kranok Thai arts. Use the tokens <knt-style> style in your prompts for the effect.

Example Results

Prompt used: "a colourful masterpiece thai cat in <knt-style> style, high-quality, professional art, realistic, thai style"

Prompt used: "a colourful masterpiece thai dog in <knt-style> style, high-quality, professional art, realistic, thai style"

🧨 Diffusers

This model can be used just like any other Stable Diffusion model. For more information, please have a look at the Stable Diffusion.

You can also export the model to ONNX, MPS and/or FLAX/JAX.

pip install torch diffusers accelerate pillow

python

from diffusers import StableDiffusionPipeline
import torch
from PIL import Image

def image_grid(imgs, rows, cols):
    assert len(imgs) == rows*cols

    w, h = imgs[0].size
    grid = Image.new('RGB', size=(cols*w, rows*h))
    grid_w, grid_h = grid.size

    for i, img in enumerate(imgs):
        grid.paste(img, box=(i%cols*w, i//cols*h))
    return grid

model_id = "CHAITron/KranokThaiV1"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "a colourful masterpiece thai dog in <knt-style> style, high-quality, professional art, realistic, thai style"

num_samples = 4
num_rows = 1

all_images = []
for _ in range(num_rows):
    images = pipe(prompt, num_images_per_prompt=num_samples, num_inference_steps=25, guidance_scale=9).images
    all_images.extend(images)

grid = image_grid(all_images, num_rows, num_samples)
grid

License

This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage. The CreativeML OpenRAIL License specifies:

You can't use the model to deliberately produce nor share illegal or harmful outputs or content
The authors claims no rights on the outputs you generate, you are free to use them and are accountable for their use which must not go against the provisions set in the license
You may re-distribute the weights and use the model commercially and/or as a service. If you do, please be aware you have to include the same use restrictions as the ones in the license and share a copy of the CreativeML OpenRAIL-M to all your users (please read the license entirely and carefully) Please read the full license here