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import os |
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os.system("pip install gradio transformers torch") |
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from transformers import T5Tokenizer, T5ForConditionalGeneration |
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import gradio as gr |
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model = T5ForConditionalGeneration.from_pretrained("./Ruttoni_AI") |
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tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-base") |
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print("Model loaded!") |
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def generate_summary(input_text): |
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input_ids = tokenizer.encode(input_text, return_tensors='pt') |
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outputs = model.generate(input_ids) |
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summary = tokenizer.decode(outputs[0], skip_special_tokens=True) |
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return summary |
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ai = gr.Interface(fn=generate_summary, inputs="text", outputs="text") |
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ai.launch() |
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print("Interface Started!") |
