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| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
| import gradio as gr | |
| tokenizer = AutoTokenizer.from_pretrained("merve/chatgpt-prompt-generator-v12") | |
| model = AutoModelForSeq2SeqLM.from_pretrained("merve/chatgpt-prompt-generator-v12", 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. photographer", value = "photographer") | |
| output_component = gr.Textbox(label = "Prompt") | |
| examples = [["photographer"], ["developer"]] | |
| description = "Cette application génère des prompts ChatGPT, elle est basée sur un modèle BART entraîné sur [ces données] (https://huggingface.co/datasets/fka/awesome-chatgpt-prompts). 📓 Il suffit d'entrer un rôle sur lequel vous voulez que le prompt soit générée. 🧙🏻🧑🏻🚀🧑🏻🎨🧑🏻🔬🧑🏻💻🧑🏼🏫🧑🏽🌾" | |
| gr.Interface(generate, inputs = input_component, outputs=output_component, examples=examples, title = "👨🏻🎤 ChatGPT Prompt Generator v12 👨🏻🎤", description=description).launch() | |