multimodalart HF staff commited on
Commit
bfcac1a
1 Parent(s): 36c9e2e

Update app.py

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Files changed (1) hide show
  1. app.py +1 -3
app.py CHANGED
@@ -9,14 +9,12 @@ from transformers import CLIPTextModel, CLIPTokenizer,T5EncoderModel, T5Tokenize
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  dtype = torch.bfloat16
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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- pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16, revision="refs/pr/3").to(device)
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-
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  MAX_SEED = np.iinfo(np.int32).max
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  MAX_IMAGE_SIZE = 2048
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  @spaces.GPU()
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  def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, guidance_scale=5.0, num_inference_steps=28, progress=gr.Progress(track_tqdm=True)):
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- pipe.to("cuda")
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  if randomize_seed:
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  seed = random.randint(0, MAX_SEED)
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  generator = torch.Generator().manual_seed(seed)
 
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  dtype = torch.bfloat16
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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  MAX_SEED = np.iinfo(np.int32).max
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  MAX_IMAGE_SIZE = 2048
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  @spaces.GPU()
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  def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, guidance_scale=5.0, num_inference_steps=28, progress=gr.Progress(track_tqdm=True)):
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+ pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16, revision="refs/pr/3").to("cuda")
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  if randomize_seed:
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  seed = random.randint(0, MAX_SEED)
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  generator = torch.Generator().manual_seed(seed)