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| from transformers import pipeline, set_seed | |
| from transformers import BioGptTokenizer, BioGptForCausalLM | |
| import gradio as gr | |
| model = BioGptForCausalLM.from_pretrained("microsoft/biogpt") | |
| tokenizer = BioGptTokenizer.from_pretrained("microsoft/biogpt") | |
| generator = pipeline('text-generation', model=model, tokenizer=tokenizer) | |
| set_seed(42) | |
| def predict(text): | |
| return generator(text, max_length=20, num_return_sequences=1, do_sample=True) | |
| interface = gr.Interface(predict, "textbox", "textbox", title="Biogpt", description="Biogpt") | |
| interface.launch() |