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ryanzhangfan commited on
Commit
887782d
1 Parent(s): 6380db8

Update app.py

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Files changed (1) hide show
  1. app.py +10 -3
app.py CHANGED
@@ -24,6 +24,8 @@ subprocess.run(
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  shell=True,
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  )
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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  # Model paths
@@ -39,7 +41,7 @@ gen_model = AutoModelForCausalLM.from_pretrained(
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  torch_dtype=torch.bfloat16,
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  attn_implementation="flash_attention_2",
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  trust_remote_code=True,
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- ).to(device)
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  # Emu3-Chat model and processor
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  chat_model = AutoModelForCausalLM.from_pretrained(
@@ -48,7 +50,7 @@ chat_model = AutoModelForCausalLM.from_pretrained(
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  torch_dtype=torch.bfloat16,
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  attn_implementation="flash_attention_2",
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  trust_remote_code=True,
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- ).to(device)
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  tokenizer = AutoTokenizer.from_pretrained(EMU_CHAT_HUB, trust_remote_code=True)
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  image_processor = AutoImageProcessor.from_pretrained(
@@ -56,11 +58,16 @@ image_processor = AutoImageProcessor.from_pretrained(
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  )
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  image_tokenizer = AutoModel.from_pretrained(
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  VQ_HUB, device_map="cpu", trust_remote_code=True
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- ).eval().to(device)
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  processor = Emu3Processor(
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  image_processor, image_tokenizer, tokenizer
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  )
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  @spaces.GPU(duration=300)
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  def generate_image(prompt):
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  POSITIVE_PROMPT = " masterpiece, film grained, best quality."
 
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  shell=True,
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  )
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+ print(gr.__version__)
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+
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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  # Model paths
 
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  torch_dtype=torch.bfloat16,
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  attn_implementation="flash_attention_2",
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  trust_remote_code=True,
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+ )
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  # Emu3-Chat model and processor
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  chat_model = AutoModelForCausalLM.from_pretrained(
 
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  torch_dtype=torch.bfloat16,
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  attn_implementation="flash_attention_2",
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  trust_remote_code=True,
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+ )
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  tokenizer = AutoTokenizer.from_pretrained(EMU_CHAT_HUB, trust_remote_code=True)
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  image_processor = AutoImageProcessor.from_pretrained(
 
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  )
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  image_tokenizer = AutoModel.from_pretrained(
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  VQ_HUB, device_map="cpu", trust_remote_code=True
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+ ).eval()
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  processor = Emu3Processor(
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  image_processor, image_tokenizer, tokenizer
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  )
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+ print(device)
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+ gen_model.to(device)
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+ chat_model.to(device)
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+ image_tokenizer.to(device)
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+
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  @spaces.GPU(duration=300)
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  def generate_image(prompt):
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  POSITIVE_PROMPT = " masterpiece, film grained, best quality."