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import os |
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os.system("pip install transformers torch psutil") |
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result = os.system("pip install transformers") |
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from transformers import pipeline |
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import gradio as gr |
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import psutil |
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def get_memory_usage(): |
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process = psutil.Process() |
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memory_usage = process.memory_info().rss / 1024 / 1024 |
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return f"Memory Usage: {memory_usage:.2f} MB" |
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generator = pipeline("text-generation", model="abeja/gpt-neox-japanese-2.7b") |
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def generate_text(prompt): |
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generated = generator( |
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prompt, |
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max_length=300, |
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do_sample=True, |
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num_return_sequences=3, |
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top_p=0.95, |
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top_k=50 |
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) |
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return generated |
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iface = gr.Interface(fn=generate_text, inputs="text", outputs="list", description=get_memory_usage(),) |
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iface.launch() |
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