openvino-static

#5
by echarlaix HF staff - opened
Files changed (2) hide show
  1. app.py +16 -17
  2. requirements.txt +5 -1
app.py CHANGED
@@ -5,20 +5,21 @@ import re
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  import torch
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  from transformers import AutoModelWithLMHead, AutoTokenizer, pipeline, set_seed
 
8
 
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- import gradio as grad
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- from diffusers import StableDiffusionPipeline
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- tokenizer = AutoTokenizer.from_pretrained("shahp7575/gpt2-horoscopes")
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- model = AutoModelWithLMHead.from_pretrained("shahp7575/gpt2-horoscopes")
 
 
 
 
 
 
 
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  def fn(sign, cat):
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- sign = "scorpio"
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-
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  prompt = f"<|category|> {cat} <|horoscope|> {sign}"
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-
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-
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-
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  prompt_encoded = torch.tensor(tokenizer.encode(prompt)).unsqueeze(0)
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  sample_outputs = model.generate(
@@ -29,18 +30,16 @@ def fn(sign, cat):
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  top_p=0.95,
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  temperature=0.95,
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  num_beams=4,
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- num_return_sequences=4,
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  )
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  final_out = tokenizer.decode(sample_outputs[0], skip_special_tokens=True)
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  starting_text = " ".join(final_out.split(" ")[4:])
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- pipe = pipeline("text-generation", model="Gustavosta/MagicPrompt-Stable-Diffusion", tokenizer="gpt2")
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-
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  seed = random.randint(100, 1000000)
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  set_seed(seed)
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- response = pipe(starting_text + " " + sign + " art.", max_length=(len(starting_text) + random.randint(60, 90)), num_return_sequences=1)
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- pipe = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
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- image = pipe(response[0]["generated_text"], num_inference_steps=5).images[0]
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  return [image, starting_text]
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@@ -52,7 +51,7 @@ with block:
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  with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True):
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  text = gr.Dropdown(
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  label="Star Sign",
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- choices=["aries", "taurus","gemini", "cancer", "leo", "virgo", "libra", "scorpio", "sagittarius", "capricorn", "aquarius", "Pisces"],
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  show_label=True,
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  max_lines=1,
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  placeholder="Enter your prompt",
@@ -64,7 +63,7 @@ with block:
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  )
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  text2 = gr.Dropdown(
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- choices=["love", "career", "wellness"],
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  label="Category",
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  show_label=True,
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  max_lines=1,
 
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  import torch
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  from transformers import AutoModelWithLMHead, AutoTokenizer, pipeline, set_seed
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+ from optimum.intel.openvino import OVStableDiffusionPipeline
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+ horoscope_model_id = "shahp7575/gpt2-horoscopes"
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+ tokenizer = AutoTokenizer.from_pretrained(horoscope_model_id)
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+ model = AutoModelWithLMHead.from_pretrained(horoscope_model_id)
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+ text_generation_pipe = pipeline("text-generation", model="Gustavosta/MagicPrompt-Stable-Diffusion", tokenizer="gpt2")
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+ stable_diffusion_pipe = OVStableDiffusionPipeline.from_pretrained("echarlaix/stable-diffusion-v1-5-openvino", revision="fp16", compile=False)
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+ height = 128
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+ width = 128
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+ stable_diffusion_pipe.reshape(batch_size=1, height=height, width=width, num_images_per_prompt=1)
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+ stable_diffusion_pipe.compile()
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  def fn(sign, cat):
 
 
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  prompt = f"<|category|> {cat} <|horoscope|> {sign}"
 
 
 
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  prompt_encoded = torch.tensor(tokenizer.encode(prompt)).unsqueeze(0)
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  sample_outputs = model.generate(
 
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  top_p=0.95,
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  temperature=0.95,
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  num_beams=4,
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+ num_return_sequences=1,
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  )
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  final_out = tokenizer.decode(sample_outputs[0], skip_special_tokens=True)
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  starting_text = " ".join(final_out.split(" ")[4:])
 
 
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  seed = random.randint(100, 1000000)
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  set_seed(seed)
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+ response = text_generation_pipe(starting_text + " " + sign + " art", max_length=(len(starting_text) + random.randint(60, 90)), num_return_sequences=1)
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+ image = stable_diffusion_pipe(response[0]["generated_text"], height=height, width=width, num_inference_steps=30).images[0]
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+
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  return [image, starting_text]
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  with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True):
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  text = gr.Dropdown(
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  label="Star Sign",
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+ choices=["Aries", "Taurus","Gemini", "Cancer", "Leo", "Virgo", "Libra", "Scorpio", "Sagittarius", "Capricorn", "Aquarius", "Pisces"],
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  show_label=True,
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  max_lines=1,
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  placeholder="Enter your prompt",
 
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  )
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  text2 = gr.Dropdown(
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+ choices=["Love", "Career", "Wellness"],
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  label="Category",
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  show_label=True,
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  max_lines=1,
requirements.txt CHANGED
@@ -1,3 +1,7 @@
1
  transformers
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  torch
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- diffusers
 
 
 
 
 
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  transformers
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  torch
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+ diffusers
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+ onnx
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+ onnxruntime
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+ openvino
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+ optimum-intel