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import gradio as gr |
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from transformers import AutoTokenizer |
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from transformers import AutoModelForSeq2SeqLM |
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tokenizer = AutoTokenizer.from_pretrained("elvish-translator-quenya-t5-small") |
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model = AutoModelForSeq2SeqLM.from_pretrained("elvish-translator-quenya-t5-small") |
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def greet(name): |
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inputs = tokenizer(text, return_tensors="pt").input_ids |
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outputs = model.generate(inputs, max_new_tokens=40, do_sample=True, top_k=30, top_p=0.95) |
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result = tokenizer.decode(outputs[0], skip_special_tokens=True) |
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return result |
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demo = gr.Interface(fn=greet, inputs="text", outputs="text") |
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demo.launch() |
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