Quentin Gallouédec commited on
Commit
bcba9c0
·
1 Parent(s): 1a49562

update app

Browse files
Files changed (1) hide show
  1. app.py +22 -11
app.py CHANGED
@@ -1,6 +1,7 @@
1
  import gradio as gr
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- from transformers import pipeline
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  from huggingface_hub import HfApi, ModelFilter
 
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  # Get the list of models from the Hugging Face Hub
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  api = HfApi()
@@ -12,31 +13,41 @@ model_pipelines = {}
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  # Load a default model initially
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  default_model_name = "gia-project/gia2-small-untrained"
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- default_generator = pipeline("text-generation", model=default_model_name, trust_remote_code=True)
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- model_pipelines[default_model_name] = default_generator
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  def generate_text(model_name, input_text):
 
 
 
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  # Check if the selected model is already loaded
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  if model_name not in model_pipelines:
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  # Load the model and create a pipeline if it's not already loaded
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  generator = pipeline("text-generation", model=model_name, trust_remote_code=True)
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  model_pipelines[model_name] = generator
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-
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- # Get the pipeline for the selected model and generate text
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  generator = model_pipelines[model_name]
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- generated_text = generator(input_text)[0]['generated_text']
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- return generated_text
 
 
 
 
 
 
 
 
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  # Define the Gradio interface
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  iface = gr.Interface(
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  fn=generate_text, # Function to be called on user input
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  inputs=[
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- gr.inputs.Dropdown(choices=models_names, label="Select Model", default=default_model_name), # Dropdown to select model
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- gr.inputs.Textbox(lines=5, label="Input Text") # Textbox for entering text
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  ],
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- outputs=gr.outputs.Textbox(label="Generated Text"), # Textbox to display the generated text
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  title="GIA Text Generation", # Title of the interface
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  )
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  # Launch the Gradio interface
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- iface.launch()
 
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  import gradio as gr
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+ from gradio.components import Dropdown, Textbox
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  from huggingface_hub import HfApi, ModelFilter
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+ from transformers import pipeline
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  # Get the list of models from the Hugging Face Hub
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  api = HfApi()
 
13
 
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  # Load a default model initially
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  default_model_name = "gia-project/gia2-small-untrained"
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+
 
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  def generate_text(model_name, input_text):
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+ # Inform the user that the model is loading
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+ yield "Loading model..."
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+
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  # Check if the selected model is already loaded
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  if model_name not in model_pipelines:
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  # Load the model and create a pipeline if it's not already loaded
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  generator = pipeline("text-generation", model=model_name, trust_remote_code=True)
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  model_pipelines[model_name] = generator
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+
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+ # Get the pipeline for the selected model
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  generator = model_pipelines[model_name]
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+
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+ # Inform the user that the text is being generated
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+ yield "Generating text..."
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+
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+ # Generate text
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+ generated_text = generator(input_text)[0]["generated_text"]
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+
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+ # Return the generated text
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+ yield generated_text
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+
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  # Define the Gradio interface
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  iface = gr.Interface(
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  fn=generate_text, # Function to be called on user input
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  inputs=[
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+ Dropdown(models_names, label="Select Model", value="gia-project/gia2-small-untrained"), # Select model
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+ Textbox(lines=5, label="Input Text"), # Textbox for entering text
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  ],
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+ outputs=Textbox(label="Generated Text"), # Textbox to display the generated text
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  title="GIA Text Generation", # Title of the interface
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  )
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  # Launch the Gradio interface
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+ iface.launch(enable_queue=True)