stable-diffusion-3.5-large-alchemist

45

9

1 language

license:apache-2.0

by

yandex

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Quick Summary

Stable Diffusion 3.5 Large Alchemist is finetuned version of Stable Diffusion 3.5 Large on Alchemist dataset, proposed in the research paper "Alchemist: Turning...

Code Examples

Using with Diffuserspythonpytorch

import torch
from diffusers import StableDiffusion3Pipeline

pipe = StableDiffusion3Pipeline.from_pretrained("yandex/stable-diffusion-3.5-large-alchemist", torch_dtype=torch.bfloat16)
pipe = pipe.to("cuda")
image = pipe(
    "a man standing under a tree",
    num_inference_steps=28,
    guidance_scale=3.5,
).images[0]
image.save("man.png")

Using with Diffuserspythonpytorch

import torch
from diffusers import StableDiffusion3Pipeline

pipe = StableDiffusion3Pipeline.from_pretrained("yandex/stable-diffusion-3.5-large-alchemist", torch_dtype=torch.bfloat16)
pipe = pipe.to("cuda")
image = pipe(
    "a man standing under a tree",
    num_inference_steps=28,
    guidance_scale=3.5,
).images[0]
image.save("man.png")

Using with Diffuserspythonpytorch

import torch
from diffusers import StableDiffusion3Pipeline

pipe = StableDiffusion3Pipeline.from_pretrained("yandex/stable-diffusion-3.5-large-alchemist", torch_dtype=torch.bfloat16)
pipe = pipe.to("cuda")
image = pipe(
    "a man standing under a tree",
    num_inference_steps=28,
    guidance_scale=3.5,
).images[0]
image.save("man.png")

Using with Diffuserspythonpytorch

import torch
from diffusers import StableDiffusion3Pipeline

pipe = StableDiffusion3Pipeline.from_pretrained("yandex/stable-diffusion-3.5-large-alchemist", torch_dtype=torch.bfloat16)
pipe = pipe.to("cuda")
image = pipe(
    "a man standing under a tree",
    num_inference_steps=28,
    guidance_scale=3.5,
).images[0]
image.save("man.png")

Using with Diffuserspythonpytorch

import torch
from diffusers import StableDiffusion3Pipeline

pipe = StableDiffusion3Pipeline.from_pretrained("yandex/stable-diffusion-3.5-large-alchemist", torch_dtype=torch.bfloat16)
pipe = pipe.to("cuda")
image = pipe(
    "a man standing under a tree",
    num_inference_steps=28,
    guidance_scale=3.5,
).images[0]
image.save("man.png")

Using with Diffuserspythonpytorch

import torch
from diffusers import StableDiffusion3Pipeline

pipe = StableDiffusion3Pipeline.from_pretrained("yandex/stable-diffusion-3.5-large-alchemist", torch_dtype=torch.bfloat16)
pipe = pipe.to("cuda")
image = pipe(
    "a man standing under a tree",
    num_inference_steps=28,
    guidance_scale=3.5,
).images[0]
image.save("man.png")

Using with Diffuserspythonpytorch

import torch
from diffusers import StableDiffusion3Pipeline

pipe = StableDiffusion3Pipeline.from_pretrained("yandex/stable-diffusion-3.5-large-alchemist", torch_dtype=torch.bfloat16)
pipe = pipe.to("cuda")
image = pipe(
    "a man standing under a tree",
    num_inference_steps=28,
    guidance_scale=3.5,
).images[0]
image.save("man.png")

Using with Diffuserspythonpytorch

import torch
from diffusers import StableDiffusion3Pipeline

pipe = StableDiffusion3Pipeline.from_pretrained("yandex/stable-diffusion-3.5-large-alchemist", torch_dtype=torch.bfloat16)
pipe = pipe.to("cuda")
image = pipe(
    "a man standing under a tree",
    num_inference_steps=28,
    guidance_scale=3.5,
).images[0]
image.save("man.png")

Using with Diffuserspythonpytorch

import torch
from diffusers import StableDiffusion3Pipeline

pipe = StableDiffusion3Pipeline.from_pretrained("yandex/stable-diffusion-3.5-large-alchemist", torch_dtype=torch.bfloat16)
pipe = pipe.to("cuda")
image = pipe(
    "a man standing under a tree",
    num_inference_steps=28,
    guidance_scale=3.5,
).images[0]
image.save("man.png")

Using with Diffuserspythonpytorch

import torch
from diffusers import StableDiffusion3Pipeline

pipe = StableDiffusion3Pipeline.from_pretrained("yandex/stable-diffusion-3.5-large-alchemist", torch_dtype=torch.bfloat16)
pipe = pipe.to("cuda")
image = pipe(
    "a man standing under a tree",
    num_inference_steps=28,
    guidance_scale=3.5,
).images[0]
image.save("man.png")

Using with Diffuserspythonpytorch

import torch
from diffusers import StableDiffusion3Pipeline

pipe = StableDiffusion3Pipeline.from_pretrained("yandex/stable-diffusion-3.5-large-alchemist", torch_dtype=torch.bfloat16)
pipe = pipe.to("cuda")
image = pipe(
    "a man standing under a tree",
    num_inference_steps=28,
    guidance_scale=3.5,
).images[0]
image.save("man.png")

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