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import gradio as gr |
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from transformers import AutoTokenizer |
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from transformers import AutoModelForCausalLM |
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tokenizer = AutoTokenizer.from_pretrained("Aityz/reviews_model") |
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model = AutoModelForCausalLM.from_pretrained("Aityz/reviews_model") |
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def aityz(Input, Tokens, TopK, TopP): |
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prompt = Input |
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inputs = tokenizer(prompt, return_tensors="pt").input_ids |
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outputs = model.generate(inputs, max_new_tokens=Tokens, do_sample=True, top_k=int(TopK), top_p=TopP) |
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output = tokenizer.batch_decode(outputs, skip_special_tokens=True) |
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outputstr = ''.join(output) |
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return(outputstr) |
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demo = gr.Interface(fn=aityz, inputs=["textbox", gr.Slider(1, 1000, value=100), gr.Number(value=50), gr.Number(value=0.95) ], outputs="textbox") |
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demo.launch() |
