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Update app.py
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app.py
CHANGED
@@ -9,7 +9,9 @@ model = T5ForConditionalGeneration.from_pretrained("ClueAI/ChatYuan-large-v2")
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device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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model.to(device)
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def preprocess(text):
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text = text.replace("\n", "\\n").replace("\t", "\\t")
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return text
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@@ -17,6 +19,7 @@ def postprocess(text):
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return text.replace("\\n", "\n").replace("\\t", "\t").replace('%20',' ')#.replace(" ", " ")
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generate_config = {'do_sample': True, 'top_p': 0.9, 'top_k': 50, 'temperature': 0.7,
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'num_beams': 1, 'max_length': 1024, 'min_length': 3, 'no_repeat_ngram_size': 5,
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'length_penalty': 0.6, 'return_dict_in_generate': True, 'output_scores': True}
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device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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model.to(device)
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base_info = "用户:你是谁?\n小元:我是元语智能公司研发的AI智能助手, 在不违反原则的情况下,我可以回答你的任何问题。"
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def preprocess(text):
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text = f"{base_info}{text}"
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text = text.replace("\n", "\\n").replace("\t", "\\t")
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return text
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return text.replace("\\n", "\n").replace("\\t", "\t").replace('%20',' ')#.replace(" ", " ")
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generate_config = {'do_sample': True, 'top_p': 0.9, 'top_k': 50, 'temperature': 0.7,
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'num_beams': 1, 'max_length': 1024, 'min_length': 3, 'no_repeat_ngram_size': 5,
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'length_penalty': 0.6, 'return_dict_in_generate': True, 'output_scores': True}
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