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import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
# تحميل الموديل
model_name = "deepseek-ai/deepseek-coder-1.3b-base"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name).to("cpu")
# دالة توليد الكود
def generate_code(prompt):
inputs = tokenizer(prompt, return_tensors="pt").to("cpu")
outputs = model.generate(
**inputs,
max_new_tokens=200, # طول الكود الناتج
temperature=0.7, # درجة الإبداع
do_sample=True,
top_k=50,
top_p=0.95
)
code = tokenizer.decode(outputs[0], skip_special_tokens=True)
return code[len(prompt):] if code.startswith(prompt) else code
# واجهة Gradio
gr.Interface(
fn=generate_code,
inputs=gr.Textbox(lines=5, placeholder="Describe what code you want...", label="Prompt"),
outputs=gr.Textbox(label="Generated Code"),
title="Code Generator - DeepSeek Model",
description="Generate Python code from a text description using DeepSeek Coder 1.3B Base model"
).launch()
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