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Update app.py
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app.py
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import gradio as gr
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from transformers import pipeline
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MODEL_ID = "hasmar03/mt5_id2md"
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def translate(direction, text, max_new_tokens=64):
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if not text.strip():
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return ""
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prompt = f"translate {direction}: {text}"
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out =
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return out
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with gr.Blocks() as demo:
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gr.Markdown("# mT5 id↔md Translator (HF Space API)")
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direction = gr.Dropdown(["id2md", "md2id"], value="id2md", label="Arah")
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inp
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max_tok
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out
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btn
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btn.click(translate, [direction, inp, max_tok], [out], api_name="translate")
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gr.Examples([["id2md","ia terus pulang begitu saja",64],
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["md2id","tarrus i pole tia",64]], [direction, inp, max_tok])
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if __name__ == "__main__":
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demo.launch()
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import gradio as gr
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from functools import lru_cache
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from transformers import pipeline
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MODEL_ID = "hasmar03/mt5_id2md"
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@lru_cache(maxsize=1)
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def get_pipe():
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return pipeline(
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"text2text-generation",
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model=MODEL_ID,
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tokenizer=MODEL_ID,
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device=-1, # CPU
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)
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def translate(direction, text, max_new_tokens=64):
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if not text.strip():
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return ""
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prompt = f"translate {direction}: {text}"
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out = get_pipe()(
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prompt,
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num_beams=4,
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do_sample=False,
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max_new_tokens=int(max_new_tokens),
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)[0]["generated_text"]
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return out
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with gr.Blocks(title="mT5 id↔md Translator (HF Space API)") as demo:
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gr.Markdown("# mT5 id↔md Translator (HF Space API)")
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direction = gr.Dropdown(["id2md", "md2id"], value="id2md", label="Arah")
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inp = gr.Textbox(label="Teks sumber", lines=3)
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max_tok = gr.Slider(16, 128, value=64, step=1, label="max_new_tokens")
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out = gr.Textbox(label="Terjemahan", lines=3)
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btn = gr.Button("Terjemahkan")
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btn.click(translate, [direction, inp, max_tok], [out], api_name="translate")
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gr.Examples(
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[["id2md", "ia terus pulang begitu saja", 64],
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["md2id", "tarrus i pole tia", 64]],
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[direction, inp, max_tok],
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[out]
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)
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demo.queue(concurrency_count=1, max_size=12)
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if __name__ == "__main__":
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demo.launch()
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