multimodalart HF staff commited on
Commit
9132934
1 Parent(s): a6e6764

Testing a max queue size of 10

Browse files

And some comments and text changing

Files changed (1) hide show
  1. app.py +7 -2
app.py CHANGED
@@ -10,17 +10,22 @@ import re
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  model_id = "CompVis/stable-diffusion-v1-4"
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  device = "cuda"
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  pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=True, revision="fp16", torch_dtype=torch.float16)
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  pipe = pipe.to(device)
 
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  word_list_dataset = load_dataset("stabilityai/word-list", data_files="list.txt", use_auth_token=True)
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  word_list = word_list_dataset["train"]['text']
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  def infer(prompt, samples, steps, scale, seed):
 
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  for filter in word_list:
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  if re.search(rf"\b{filter}\b", prompt):
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  raise gr.Error("Unsafe content found. Please try again with different prompts.")
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  generator = torch.Generator(device=device).manual_seed(seed)
 
 
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  with autocast("cuda"):
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  images_list = pipe(
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  [prompt] * samples,
@@ -160,7 +165,7 @@ examples = [
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  1024,
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  ],
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  [
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- "A small cabin on top of a snowy mountain in the style of disney, arstation",
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  4,
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  45,
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  7,
@@ -300,4 +305,4 @@ Despite how impressive being able to turn text into image is, beware to the fact
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  """
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  )
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- block.queue(max_size=40).launch()
 
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  model_id = "CompVis/stable-diffusion-v1-4"
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  device = "cuda"
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+ #If you are running this code locally, you need to either do a 'huggingface-cli login` or paste your User Access Token from here https://huggingface.co/settings/tokens into the use_auth_token field below.
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  pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=True, revision="fp16", torch_dtype=torch.float16)
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  pipe = pipe.to(device)
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+ #When running locally, you won`t have access to this, so you can remove this part
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  word_list_dataset = load_dataset("stabilityai/word-list", data_files="list.txt", use_auth_token=True)
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  word_list = word_list_dataset["train"]['text']
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  def infer(prompt, samples, steps, scale, seed):
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+ #When running locally you can also remove this filter
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  for filter in word_list:
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  if re.search(rf"\b{filter}\b", prompt):
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  raise gr.Error("Unsafe content found. Please try again with different prompts.")
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  generator = torch.Generator(device=device).manual_seed(seed)
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+
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+ #If you are running locally with CPU, you can remove the `with autocast("cuda")`
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  with autocast("cuda"):
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  images_list = pipe(
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  [prompt] * samples,
 
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  1024,
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  ],
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  [
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+ "A small cabin on top of a snowy mountain in the style of Disney, artstation",
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  4,
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  45,
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  7,
 
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  """
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  )
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+ block.queue(max_size=10).launch()