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import gradio as gr |
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import torch |
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import transformers |
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from transformers import AutoTokenizer, AutoModelForCausalLM, set_seed |
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set_seed(42) |
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tokenizer = AutoTokenizer.from_pretrained("togethercomputer/RedPajama-INCITE-Chat-3B-v1") |
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model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-INCITE-Chat-3B-v1", torch_dtype=torch.bfloat16) |
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def Bemenet(bemenet): |
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prompt = "<human>: Who is Alan Turing?\n<bot>:" |
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inputs = tokenizer(prompt, return_tensors='pt').to(model.device) |
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input_length = inputs.input_ids.shape[1] |
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outputs = model.generate( |
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**inputs, max_new_tokens=128, do_sample=True, temperature=0.7, top_p=0.7, top_k=50, return_dict_in_generate=True |
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) |
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token = outputs.sequences[0, input_length:] |
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output_str = tokenizer.decode(token) |
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return output_str |
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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() |