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@@ -72,9 +72,9 @@ Usage
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  import torch
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  from transformers import T5Tokenizer, AutoModelForSeq2SeqLM
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- tokenizer = T5Tokenizer.from_pretrained("yuyijiong/Randeng-T5-large-sentiment-analysis-Chinese")
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- model = AutoModelForSeq2SeqLM.from_pretrained("yuyijiong/Randeng-T5-large-sentiment-analysis-Chinese", device_map="auto")
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- generation_config=GenerationConfig.from_pretrained("yuyijiong/Randeng-T5-large-sentiment-analysis-Chinese")
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  text = '情感四元组(对象 | 观点 | 方面 | 极性)抽取任务(观点可以较长): [个头大、口感不错,就是个别坏了的或者有烂掉口子刻意用泥土封着,这样做不好。]'
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  input_ids = tokenizer(text,return_tensors="pt", padding=True)['input_ids'].cuda(0)
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  with torch.no_grad():
 
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  import torch
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  from transformers import T5Tokenizer, AutoModelForSeq2SeqLM
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+ tokenizer = T5Tokenizer.from_pretrained("yuyijiong/T5-large-sentiment-analysis-Chinese")
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+ model = AutoModelForSeq2SeqLM.from_pretrained("yuyijiong/T5-large-sentiment-analysis-Chinese", device_map="auto")
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+ generation_config=GenerationConfig.from_pretrained("yuyijiong/T5-large-sentiment-analysis-Chinese")
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  text = '情感四元组(对象 | 观点 | 方面 | 极性)抽取任务(观点可以较长): [个头大、口感不错,就是个别坏了的或者有烂掉口子刻意用泥土封着,这样做不好。]'
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  input_ids = tokenizer(text,return_tensors="pt", padding=True)['input_ids'].cuda(0)
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  with torch.no_grad():