Update README.md

README.md

@@ -17,7 +17,7 @@ tags:
 
 ## Introduction
 
-QwQ is the reasoning model of Qwen series. Compared with conventional instruction-tuned models QwQ which is capable of thinking and reasoning can achieve significantly enhanced performance in downstream tasks espeically hard problems. QwQ-32B is the medium-size reasoning model, which is capable of achieving competitive performance against state-of-the art reasoning models, e.g., DeepSeek-R1, o1-mini. 
+QwQ is the reasoning model of the Qwen series. Compared with conventional instruction-tuned models, QwQ, which is capable of thinking and reasoning, can achieve significantly enhanced performance in downstream tasks, especially hard problems. QwQ-32B is the medium-sized reasoning model, which is capable of achieving competitive performance against state-of-the-art reasoning models, e.g., DeepSeek-R1, o1-mini.
 
 **This repo contains the AWQ-quantized 4-bit QwQ 32B model**, which has the following features:
 - Type: Causal Language Models
@@ -71,10 +71,6 @@ text = tokenizer.apply_chat_template(
     add_generation_prompt=True
 )
 
-# avoid empty thought content by forcing the model to start with "<think>\n"
-response_prefix = "<think>\n" 
-text += response_prefix
-
 model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
 
 generated_ids = model.generate(
@@ -86,14 +82,14 @@ generated_ids = [
 ]
 
 response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
-print(response_prefix + response)
+print(response)
 ```
 
 ### Usage Guidelines
 
 To achieve optimal performance, we recommend the following settings:
 
-1. **Enforce Thoughtful Output**: Ensure the model starts with "\<think\>\n" to prevent generating empty thinking content, which can degrade output quality.
+1. **Enforce Thoughtful Output**: Ensure the model starts with "\<think\>\n" to prevent generating empty thinking content, which can degrade output quality. If you use `apply_chat_template` and set `add_generation_prompt=True`, this is already automatically implemented, but it may cause the response to lack the \<think\> tag at the beginning. This is normal behavior.
 
 2. **Sampling Parameters**:
    - Use Temperature=0.6 and TopP=0.95 instead of Greedy decoding to avoid endless repetitions and enhance diversity.