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import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
# ุชุญู
ูู ุงูู
ูุฏูู
model_name = "Salesforce/codegen-350M-mono"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name).to("cpu")
# ุฏุงูุฉ ุงูุชูููุฏ
def generate_code(prompt):
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=128, num_return_sequences=1)
code = tokenizer.decode(outputs[0], skip_special_tokens=True)
return code
# ูุงุฌูุฉ 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 - Mono Model",
description="Generate Python code from a text description using CodeGen-350M-Mono model"
).launch()
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