Create app.py

app.py

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+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. photographer", value = "photographer")
+output_component = gr.Textbox(label = "Prompt")
+examples = [["photographer"], ["developer"]]
+description = "This app generates ChatGPT prompts, it's based on a BART model trained on [this dataset](https://huggingface.co/datasets/fka/awesome-chatgpt-prompts). 📓 Simply enter a persona that you want the prompt to be generated based on. 🧙🏻🧑🏻‍🚀🧑🏻‍🎨🧑🏻‍🔬🧑🏻‍💻🧑🏼‍🏫🧑🏽‍🌾"
+gr.Interface(generate, inputs = input_component, outputs=output_component, examples=examples, title = "👨🏻‍🎤 ChatGPT Prompt Generator 👨🏻‍🎤", description=description).launch()