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@@ -69,10 +69,12 @@ We trained models using datasets of different sizes (200,000, 600,000, and 1,000
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  |LR_scheduler | linear |
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  ## Use model
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- BELLE can be easily loaded with AutoModelForCausalLM.
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-
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- Please note that the input should be formatted as `Human: {input} \n\nAssistant:` in both training and inference.
 
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  ``` python
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  from transformers import AutoTokenizer, AutoModelForCausalLM
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  import sys
@@ -146,6 +148,11 @@ BELLE模型以Bloomz-7b1-mt为基础,在 1.0M 条中文数据上,结合Stanf
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  |LR_scheduler | linear |
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  ## 使用模型
 
 
 
 
 
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  通过AutoModelForCausalLM即可直接载入模型并使用。
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  ``` python
 
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  |LR_scheduler | linear |
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  ## Use model
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+ Please note that the input should be formatted as follows in both **training** and **inference**.
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+ ``` python
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+ Human: {input} \n\nAssistant:
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+ ```
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+ BELLE can be easily loaded with AutoModelForCausalLM.
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  ``` python
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  from transformers import AutoTokenizer, AutoModelForCausalLM
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  import sys
 
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  |LR_scheduler | linear |
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  ## 使用模型
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+ 请注意,在训练和推理时,模型的输入应该处理成如下形式:
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+ ``` python
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+ Human: {input} \n\nAssistant:
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+ ```
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+
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  通过AutoModelForCausalLM即可直接载入模型并使用。
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  ``` python