Update README.md
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README.md
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ret = tokenizer.decode(generated_ids.sequences[0], skip_special_tokens=False)
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print(ret)
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```
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ret = tokenizer.decode(generated_ids.sequences[0], skip_special_tokens=False)
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print(ret)
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```
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## Prompt
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You could give model a style or a specific language, for example:
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```python
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inputs = tokenizer('''<|endoftext|>
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def add(a, b):
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return a + b
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# docstring
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"""
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Calculate numbers add.
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Args:
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a: the first number to add
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b: the second number to add
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Return:
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The result of a + b
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"""
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<|endoftext|>
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def load_excel(path):
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return pd.read_excel(path)
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# docstring
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"""''', return_tensors='pt')
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doc_max_length = 128
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generated_ids = model.generate(
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**inputs,
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max_length=inputs.input_ids.shape[1] + doc_max_length,
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do_sample=False,
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return_dict_in_generate=True,
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num_return_sequences=1,
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output_scores=True,
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pad_token_id=50256,
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eos_token_id=50256 # <|endoftext|>
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)
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ret = tokenizer.decode(generated_ids.sequences[0], skip_special_tokens=False)
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print(ret)
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inputs = tokenizer('''<|endoftext|>
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def add(a, b):
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return a + b
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# docstring
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"""
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计算数字相加
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Args:
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a: 第一个加数
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b: 第二个加数
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Return:
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相加的结果
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"""
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<|endoftext|>
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def load_excel(path):
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return pd.read_excel(path)
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# docstring
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"""''', return_tensors='pt')
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doc_max_length = 128
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generated_ids = model.generate(
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**inputs,
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max_length=inputs.input_ids.shape[1] + doc_max_length,
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do_sample=False,
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return_dict_in_generate=True,
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num_return_sequences=1,
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output_scores=True,
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pad_token_id=50256,
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eos_token_id=50256 # <|endoftext|>
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)
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ret = tokenizer.decode(generated_ids.sequences[0], skip_special_tokens=False)
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print(ret)
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```
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