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app.py
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import streamlit as st
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from transformers import AutoModelForCausalLM, AutoTokenizer
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# تحميل النموذج والTokenizer
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@st.cache_resource # لتخزين النموذج في الذاكرة المؤقتة
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def load_model():
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model_name = "microsoft/Phi-4-mini-instruct"
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model = AutoModelForCausalLM.from_pretrained(model_name)
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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return model, tokenizer
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model, tokenizer = load_model()
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# واجهة Streamlit
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st.title("Phi-4-mini-instruct Chatbot")
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st.write("تفاعل مع نموذج Phi-4-mini-instruct من Microsoft.")
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# إدخال النص
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user_input = st.text_input("أدخل نصك هنا:")
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# توليد النص
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if user_input:
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inputs = tokenizer(user_input, return_tensors="pt")
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outputs = model.generate(**inputs, max_new_tokens=100)
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response = tokenizer.decode(outputs[0], skip_special_tokens=True)
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st.write("النموذج يقول:", response)
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