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arjunpatel
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Commit
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658b022
1
Parent(s):
91a9511
skeleton version of demo working
Browse files- gradio_demo.py +60 -0
gradio_demo.py
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import gradio as gr
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from transformers import AutoTokenizer
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from transformers import pipeline
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model_checkpoint = "distilgpt2"
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tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
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generate = pipeline("text-generation",
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model="arjunpatel/distilgpt2-finetuned-pokemon-moves",
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tokenizer=tokenizer)
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def filter_text(generated_move):
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# removes any moves that follow after the genrated move
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print(generated_move)
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sentences = generated_move.split(".")
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if len(sentences) > 2:
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ret_set = " ".join(sentences[0:1])
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else:
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ret_set = generated_move
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return ret_set
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def create_move(move):
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seed_text = "This move is called "
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generated_move = generate(seed_text + move, num_return_sequences=2,
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no_repeat_ngram_size=4)[0]["generated_text"]
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return generated_move
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# # demo = gr.Interface(fn=greet, inputs = "text", outputs="text")
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#
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# gr.Interface(fn=create_move,
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# inputs="text", outputs="text").launch()
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# # demo.launch()
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def filler_move(test_move, temperature):
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return test_move + " with temperature " + str(temperature)
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demo = gr.Blocks()
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with demo:
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gr.Markdown("What's that Pokemon Move?")
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with gr.Tabs():
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with gr.TabItem("Standard Generation"):
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with gr.Row():
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text_input_baseline = gr.Textbox()
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text_output_baseline = gr.Textbox()
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text_button_baseline = gr.Button("Create my move!")
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with gr.TabItem("Temperature Search"):
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with gr.Row():
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temperature = gr.Slider(minimum = 0.3, maximum = 4, value = 1, step = 0.1,
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label = "Temperature")
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text_input_temp = gr.Textbox(label="Move Name")
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text_output_temp = gr.Textbox(label = "Move Description")
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text_button_temp = gr.Button("Create my move!")
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#text_button_baseline.click(filler_move, inputs=[text_input_baseline, 0], outputs=text_output_baseline)
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text_button_temp.click(filler_move, inputs=[text_input_temp, temperature], outputs=text_output_temp)
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demo.launch()
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