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Update app.py
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app.py
CHANGED
@@ -3,6 +3,9 @@ import gradio as gr
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tokenizer = AutoTokenizer.from_pretrained("merve/chatgpt-prompt-generator-v12")
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model = AutoModelForSeq2SeqLM.from_pretrained("merve/chatgpt-prompt-generator-v12", from_tf=True)
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def generate(prompt):
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@@ -10,7 +13,18 @@ def generate(prompt):
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generated_ids = model.generate(batch["input_ids"], max_new_tokens=150)
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output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
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return output[0]
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input_component = gr.Textbox(label = "Input a persona, e.g. photographer", value = "photographer")
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output_component = gr.Textbox(label = "Prompt")
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examples = [["photographer"], ["developer"]]
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tokenizer = AutoTokenizer.from_pretrained("merve/chatgpt-prompt-generator-v12")
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model = AutoModelForSeq2SeqLM.from_pretrained("merve/chatgpt-prompt-generator-v12", from_tf=True)
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#
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tokenizer2 = AutoTokenizer.from_pretrained("Kaludi/chatgpt-gpt4-prompts-bart-large-cnn-samsum")
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model2 = AutoModelForSeq2SeqLM.from_pretrained("Kaludi/chatgpt-gpt4-prompts-bart-large-cnn-samsum", from_tf=True)
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def generate(prompt):
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generated_ids = model.generate(batch["input_ids"], max_new_tokens=150)
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output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
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return output[0]
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def generate2(prompt, max_new_tokens):
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batch = tokenizer2(prompt, return_tensors="pt")
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generated_ids = model2.generate(batch["input_ids"], max_new_tokens=150)
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output = tokenizer2.batch_decode(generated_ids, skip_special_tokens=True)
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return output[0]
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def generate_prompt(type, prompt, max_new_tokens):
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if type==1:
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return generate(prompt)
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elif type==2:
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return generate2(prompt, max_new_tokens)
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#
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input_component = gr.Textbox(label = "Input a persona, e.g. photographer", value = "photographer")
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output_component = gr.Textbox(label = "Prompt")
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examples = [["photographer"], ["developer"]]
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