Yaron Koresh commited on
Commit
b6ff149
·
verified ·
1 Parent(s): e48959f

Update app.py

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Files changed (1) hide show
  1. app.py +8 -8
app.py CHANGED
@@ -25,20 +25,20 @@ import jax.numpy as jnp
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  last_motion=None
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  fps=20
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  time=3
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- width=512
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- height=512
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  device = "cuda"
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  dtype = torch.float16
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  result=[]
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- step = 2
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- accu=1
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  repo = "ByteDance/AnimateDiff-Lightning"
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  ckpt = f"animatediff_lightning_{step}step_diffusers.safetensors"
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- base = "emilianJR/epiCRealism"
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- #base = "SG161222/Realistic_Vision_V6.0_B1_noVAE"
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  #vae = AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse").to(device, dtype=dtype)
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  #unet = UNet2DConditionModel.from_config("emilianJR/epiCRealism",subfolder="unet").to(device, dtype).load_state_dict(load_file(hf_hub_download("emilianJR/epiCRealism", "unet/diffusion_pytorch_model.safetensors"), device=device), strict=False)
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- #adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-3", torch_dtype=dtype, device=device)
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  css="""
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  input, input::placeholder {
@@ -193,7 +193,7 @@ def run(i,m,p1,p2,*result):
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  return out
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- pipe = AnimateDiffPipeline.from_pretrained(base, torch_dtype=dtype).to(device)
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  pipe.scheduler = DDIMScheduler(
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  clip_sample=False,
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  beta_start=0.00085,
 
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  last_motion=None
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  fps=20
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  time=3
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+ width=896
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+ height=896
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  device = "cuda"
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  dtype = torch.float16
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  result=[]
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+ step = 4
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+ accu=2
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  repo = "ByteDance/AnimateDiff-Lightning"
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  ckpt = f"animatediff_lightning_{step}step_diffusers.safetensors"
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+ #base = "emilianJR/epiCRealism"
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+ base = "SG161222/Realistic_Vision_V6.0_B1_noVAE"
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  #vae = AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse").to(device, dtype=dtype)
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  #unet = UNet2DConditionModel.from_config("emilianJR/epiCRealism",subfolder="unet").to(device, dtype).load_state_dict(load_file(hf_hub_download("emilianJR/epiCRealism", "unet/diffusion_pytorch_model.safetensors"), device=device), strict=False)
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+ adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-3", torch_dtype=dtype, device=device)
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  css="""
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  input, input::placeholder {
 
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  return out
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+ pipe = AnimateDiffPipeline.from_pretrained(base, motion_adapter=adapter, vae=vae, torch_dtype=dtype).to(device)
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  pipe.scheduler = DDIMScheduler(
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  clip_sample=False,
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  beta_start=0.00085,