Duplicate from king007/GPT-Prompt-Generate-2
Browse filesCo-authored-by: king007 <king007@users.noreply.huggingface.co>
- .gitattributes +34 -0
- README.md +14 -0
- app.py +40 -0
- requirements.txt +3 -0
.gitattributes
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README.md
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---
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title: GPT Prompt Generate 2
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emoji: π¨π»βπ€
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colorFrom: purple
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colorTo: pink
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sdk: gradio
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sdk_version: 3.16.2
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app_file: app.py
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pinned: false
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license: apache-2.0
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duplicated_from: king007/GPT-Prompt-Generate-2
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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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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#
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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=int(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=int(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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requirements.txt
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tensorflow
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transformers
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torch
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