Update app.py

app.py

@@ -9,8 +9,8 @@ import gradio as gr
 import numpy as np
 from lxml.html import fromstring
 from pathos.threading import ThreadPool as Pool
-from diffusers import DiffusionPipeline, AnimateDiffPipeline, MotionAdapter, DDIMScheduler
-from diffusers.pipelines.flux import FluxPipeline
+from diffusers import DiffusionPipeline, AnimateDiffPipeline, MotionAdapter, EulerDiscreteScheduler
+#from diffusers.pipelines.flux import FluxPipeline
 from diffusers.utils import export_to_gif
 from huggingface_hub import hf_hub_download
 from safetensors.torch import load_file
@@ -21,27 +21,13 @@ dtype = torch.float16
 step = 2
 repo = "ByteDance/AnimateDiff-Lightning"
 ckpt = f"animatediff_lightning_{step}step_diffusers.safetensors"
-model_id = "emilianJR/epiCRealism"
+base = "emilianJR/epiCRealism"
 
 adapter = MotionAdapter().to(device, dtype)
 adapter.load_state_dict(load_file(hf_hub_download(repo ,ckpt), device=device))
+pipe = AnimateDiffPipeline.from_pretrained(base, motion_adapter=adapter, torch_dtype=dtype).to(device)
+pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing", beta_schedule="linear")
 
-pipe = AnimateDiffPipeline.from_pretrained(
-    model_id,
-    motion_adapter=adapter,
-    token=os.getenv("hf_token")
-)
-
-scheduler = DDIMScheduler.from_pretrained(
-    model_id,
-    subfolder="scheduler", 
-    clip_sample=False,
-    timestep_spacing="linspace", 
-    steps_offset=1,
-    token=os.getenv("hf_token")
-)
-
-pipe.scheduler = scheduler
 pipe.enable_vae_slicing()
 pipe.enable_vae_tiling()