Open litsh opened 1 month ago
Hi litsh, the tagger is trained with vanilla prompts and a default system prompt "You are a helpful assistant.", so no other template prompts are used for inference. For example, if you would like to tag "How are you?" then just use it as the query. Please kindly note that this is a Qwen model finetuned with the chatml format like other models in the Qwen series. So please make sure you generate prompt with proper chatml template.
Hi litsh, the tagger is trained with vanilla prompts and a default system prompt "You are a helpful assistant.", so no other template prompts are used for inference. For example, if you would like to tag "How are you?" then just use it as the query. Please kindly note that this is a Qwen model finetuned with the chatml format like other models in the Qwen series. So please make sure you generate prompt with proper chatml template.
Thanks for you reply! If I want to tag an instruction "How are you?", the full prompt feed into the model should belike which one of the below:
<|im_start|>system You are a helpful assistant.<|im_end|> <|im_start|>user How are you?<|im_end|> <|im_start|>assistant
or
<|im_start|>system You are a helpful assistant.<|im_end|> <|im_start|>user Please identify tags of user intentions in the following user query and provide an explanation for each tag. Please respond in the JSON format {"tag": str, "explanation": str}. Query: How are you? <|im_end|> <|im_start|>assistant
Hi litsh, the tagger is trained with vanilla prompts and a default system prompt "You are a helpful assistant.", so no other template prompts are used for inference. For example, if you would like to tag "How are you?" then just use it as the query. Please kindly note that this is a Qwen model finetuned with the chatml format like other models in the Qwen series. So please make sure you generate prompt with proper chatml template.
Thanks for you reply! If I want to tag an instruction "How are you?", the full prompt feed into the model should belike which one of the below:
<|im_start|>system You are a helpful assistant.<|im_end|> <|im_start|>user How are you?<|im_end|> <|im_start|>assistant
or<|im_start|>system You are a helpful assistant.<|im_end|> <|im_start|>user Please identify tags of user intentions in the following user query and provide an explanation for each tag. Please respond in the JSON format {"tag": str, "explanation": str}. Query: How are you? <|im_end|> <|im_start|>assistant
Hi, have you figured out this?
at {"tag": str, "explanation": str}. Query: How are you? <|im_end|> <|im_start|>assistant
Hi, have you figured out this? @SefaZeng Use the former one should be fine.
I see there is a Qwen-1_8B version of Instagger on ModelScope. Could you please share the prompt you used for finetuning this model so that we can obtain better results when using the tagger.