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Update app.py
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app.py
CHANGED
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@@ -7,32 +7,34 @@ model = AutoModelForSeq2SeqLM.from_pretrained("merve/chatgpt-prompt-generator-v1
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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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batch = tokenizer(prompt, return_tensors="pt")
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generated_ids = model.generate(batch["input_ids"], max_new_tokens=
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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=
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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 generate2_test(prompt):
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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(
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if
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return generate(prompt)
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elif
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return generate2(prompt, max_new_tokens)
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#
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-
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output_component = gr.Textbox(label = "Prompt")
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examples = [["photographer"], ["developer"]]
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description = ""
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gr.Interface(
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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, max_new_tokens):
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batch = tokenizer(prompt, return_tensors="pt")
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generated_ids = model.generate(batch["input_ids"], max_new_tokens=max_new_tokens)
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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=max_new_tokens)
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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 generate2_test(prompt):
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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(aitype, prompt, max_new_tokens):
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if aitype=='1':
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return generate(prompt, max_new_tokens)
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elif aitype=='2':
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return generate2(prompt, max_new_tokens)
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#
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input_aitype = gr.Textbox(label = "Input a persona, e.g. photographer", value = "2")
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input_prompt = gr.Textbox(label = "Input a persona, e.g. photographer", value = "photographer")
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input_maxtokens = gr.Textbox(label = "max tokens", value = "150")
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output_component = gr.Textbox(label = "Prompt")
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examples = [["photographer"], ["developer"]]
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description = ""
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gr.Interface(generate_prompt, inputs = [input_aitype,input_prompt,input_maxtokens], outputs=output_component, examples=examples, title = "π¨π»βπ€ ChatGPT Prompt Generator v12 π¨π»βπ€", description=description).launch()
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