| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
| import gradio as gr | |
| tokenizer = AutoTokenizer.from_pretrained("merve/chatgpt-prompts-bart-long") | |
| model = AutoModelForSeq2SeqLM.from_pretrained("merve/chatgpt-prompts-bart-long", from_tf=True) | |
| def generate(prompt): | |
| batch = tokenizer(prompt, return_tensors="pt") | |
| generated_ids = model.generate(batch["input_ids"], max_new_tokens=150) | |
| output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True) | |
| return output[0] | |
| input_component = gr.Textbox(label = "Input a persona, e.g. developer", value = "developer") | |
| output_component = gr.Textbox(label = "Prompt") | |
| examples = [["photographer"], ["developer"]] | |
| description = "This app generates βζεΏδΈθ¨β prompts π Simply enter a character setting that you want the prompt to be generated based on. π§π»π§π»βππ§π»βπ¨π§π»βπ¬π§π»βπ»π§πΌβπ«π§π½βπΎ" | |
| gr.Interface(generate, inputs = input_component, outputs=output_component, examples=examples, title = "πΊ PromptGen πΊ", description=description).launch() | |