Update app.py
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app.py
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/DeepSeek-Coder-V2-Lite-Base", trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained("deepseek-ai/DeepSeek-Coder-V2-Lite-Base", trust_remote_code=True, torch_dtype=torch.bfloat16).cuda()
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input_text = """<|fim▁begin|>def quick_sort(arr):
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if len(arr) <= 1:
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return arr
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pivot = arr[0]
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left = []
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right = []
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<|fim▁hole|>
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if arr[i] < pivot:
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left.append(arr[i])
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else:
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right.append(arr[i])
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return quick_sort(left) + [pivot] + quick_sort(right)<|fim▁end|>"""
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inputs = tokenizer(input_text, return_tensors="pt").to(model.device)
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outputs = model.generate(**inputs, max_length=128)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True)[len(input_text):])
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