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RandomNameAnd6
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Parent(s):
6b1c78b
Update app.py
Browse files
app.py
CHANGED
@@ -7,13 +7,13 @@ import random
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from transformers import GPT2Tokenizer, GPT2LMHeadModel
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tokenizer = GPT2Tokenizer.from_pretrained("gpt2-medium")
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model = GPT2LMHeadModel.from_pretrained("
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def generate_text(prompt):
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# Read real titles from file
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with open('dhar_mann_titles.txt', 'r') as file:
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@@ -21,7 +21,7 @@ with open('dhar_mann_titles.txt', 'r') as file:
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# Function to generate an AI title (dummy implementation)
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def generate_ai_title():
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inputs = tokenizer(["<|startoftext|>"]*1, return_tensors
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outputs = model.generate(**inputs, max_new_tokens=50, use_cache=True, temperature=0.85, do_sample=True)
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return (tokenizer.batch_decode(outputs)[0])[15:-13]
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@@ -48,7 +48,7 @@ def update_options():
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def create_interface():
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with gr.Blocks() as demo:
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score = gr.State(0)
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real_index_state = gr.State(0)
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score_display = gr.Markdown("## Real or AI - Dhar Mann\n**Current Score: 0**")
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@@ -87,9 +87,10 @@ def create_interface():
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continue_button.click(on_continue, inputs=score, outputs=[option1_box, option2_box, real_index_state, score_display, choice, result_text, continue_button, restart_button])
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restart_button.click(on_restart, outputs=[option1_box, option2_box, real_index_state, score_display, choice, result_text, continue_button, restart_button])
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# Set initial content for option boxes
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option1_box.value = option1
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option2_box.value = option2
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return demo
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from transformers import GPT2Tokenizer, GPT2LMHeadModel
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tokenizer = GPT2Tokenizer.from_pretrained("gpt2-medium")
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model = GPT2LMHeadModel.from_pretrained("gpt2-medium")
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def generate_text(prompt):
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input_ids = tokenizer.encode(prompt, return_tensors="pt")
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output = model.generate(input_ids, max_length=48, temperature=0.85, do_sample=True)
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text = tokenizer.decode(output[0], skip_special_tokens=True)
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return text
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# Read real titles from file
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with open('dhar_mann_titles.txt', 'r') as file:
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# Function to generate an AI title (dummy implementation)
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def generate_ai_title():
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inputs = tokenizer(["<|startoftext|>"]*1, return_tensors="pt")
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outputs = model.generate(**inputs, max_new_tokens=50, use_cache=True, temperature=0.85, do_sample=True)
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return (tokenizer.batch_decode(outputs)[0])[15:-13]
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def create_interface():
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with gr.Blocks() as demo:
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score = gr.State(0)
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real_index_state = gr.State(0) # Initialize real_index_state properly
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score_display = gr.Markdown("## Real or AI - Dhar Mann\n**Current Score: 0**")
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continue_button.click(on_continue, inputs=score, outputs=[option1_box, option2_box, real_index_state, score_display, choice, result_text, continue_button, restart_button])
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restart_button.click(on_restart, outputs=[option1_box, option2_box, real_index_state, score_display, choice, result_text, continue_button, restart_button])
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# Set initial content for option boxes and real_index_state
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option1_box.value = option1
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option2_box.value = option2
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real_index_state.set(real_index) # Set the initial real_index_state
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return demo
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