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Browse files- app.py +31 -0
- requirements.txt +2 -0
app.py
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import gradio as gr
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from transformers import pipeline, set_seed
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from transformers import AutoModelForCausalLM, AutoTokenizer
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checkpoint = "bigcode/starcoder-3b"
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device = "cpu"
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tokenizer = AutoTokenizer.from_pretrained(checkpoint)
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model = AutoModelForCausalLM.from_pretrained(checkpoint).to(device)
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generator = pipeline('text-generation', model='gpt2', return_full_text=False)
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set_seed(42)
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def Bemenet(bemenet):
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inputs = tokenizer.encode(bemenet, return_tensors="pt").to(device)
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outputs = model.generate(inputs)
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return tokenizer.decode(outputs[0])
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interface = gr.Interface(fn=Bemenet,
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title="Cím..",
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description="Leírás..",
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inputs="text",
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outputs="text")
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interface.launch()
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requirements.txt
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transformers
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tensorflow
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