| from transformers import BartForConditionalGeneration, BartTokenizer | |
| import gradio as gr | |
| # Charger le modèle BART et le tokenizer | |
| model_name = "facebook/bart-large-cnn" | |
| tokenizer = BartTokenizer.from_pretrained(model_name) | |
| model = BartForConditionalGeneration.from_pretrained(model_name) | |
| # Fonction pour générer du texte | |
| def generate_text(prompt): | |
| inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=512) | |
| summary_ids = model.generate(inputs["input_ids"], max_length=150, min_length=40, length_penalty=2.0, num_beams=4, early_stopping=True) | |
| return tokenizer.decode(summary_ids[0], skip_special_tokens=True) | |
| # Créer une interface de saisie avec Gradio | |
| interface = gr.Interface(fn=generate_text, inputs="text", outputs="text",title="TeLLMyStory",description="Enter your story idea and the model will generate the story based on it.") | |
| #Lancer l'interface | |
| interface.launch() | |