Create app.py

app.py

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+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_name = "meta-llama/Meta-Llama-3-8B"
+
+# Tokenizer ve modeli Hugging Face'den yükleyin
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Streamlit arayüzünü oluşturma
+st.title("Text Generation with LLaMA 3 8B")
+prompt = st.text_input("Enter your prompt:")
+
+if st.button("Generate"):
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(inputs["input_ids"], max_length=100)
+    generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    st.text_area("Generated Text", value=generated_text, height=200)