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from transformers import AutoTokenizer, AutoModelForCausalLM
import gradio as gr
tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-2", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("microsoft/phi-2", torch_dtype="auto", flash_attn=True, flash_rotary=True, fused_dense=True, device_map="cuda", trust_remote_code=True)
def generate(prompt, length):
inputs = tokenizer(prompt, return_tensors="pt", return_attention_mask=False)
outputs = model.generate(**inputs, max_length=length)
return tokenizer.batch_decode(outputs)[0]
demo = gr.Interface(fn=generate, inputs=["text", "number"], outputs="text")
if __name__ == "__main__":
demo.launch(show_api=False)
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