app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "CHARKA/Llama-2-7b-chat-h-maroc_edu"

# Charger le modèle et le tokenizer depuis le Hub
model = AutoModelForCausalLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

# Fonction de génération de texte
def generate_text(input_text):
    inputs = tokenizer.encode(input_text, return_tensors="pt")
    outputs = model.generate(inputs, max_length=100, num_return_sequences=1)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

# Créer l'interface Gradio
interface = gr.Interface(
    fn=generate_text,
    inputs=gr.Textbox(lines=2, placeholder="أدخل طلبك هنا"),
    outputs="text",
    title="التفاعل مع النموذج",
    description="اجهة تفاعل تستخدم نموذج توليد النصوص"
)

# Lancer l'interface
interface.launch()