From a380678a004feb5e2beb260aaeed54ca319b44e6 Mon Sep 17 00:00:00 2001
From: JustinLin610 <justinlin930319@hotmail.com>
Date: Thu, 10 Aug 2023 11:36:56 +0800
Subject: [PATCH] update faq

---
 FAQ.md    | 9 +++++++++
 FAQ_zh.md | 4 ++++
 2 files changed, 13 insertions(+)

diff --git a/FAQ.md b/FAQ.md
index b4ffe0e..c645286 100644
--- a/FAQ.md
+++ b/FAQ.md
@@ -21,6 +21,9 @@ This is the merge file of the tokenizer. You have to download it. Note that if y
 #### transformers_stream_generator/tiktoken/accelerate not found
 
 Run the command `pip install -r requirements.txt`. You can find the file at [https://github.com/QwenLM/Qwen-7B/blob/main/requirements.txt](https://github.com/QwenLM/Qwen-7B/blob/main/requirements.txt).
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+
 
 ## Demo & Inference
 
@@ -61,12 +64,18 @@ We solved this problem. Updating the code to the latest version can help.
 #### Unsatisfactory performance in processing long sequences
 
 Please ensure that NTK is applied. `use_dynamc_ntk` and `use_logn_attn` in `config.json` should be set to `true` (`true` by default).
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+
 
 ## Finetuning
 
 #### Can Qwen support SFT or even RLHF?
 
 We do not provide finetuning or RLHF codes for now. However, some projects have supported finetuning, see [FastChat](**[https://github.com/lm-sys/FastChat](https://github.com/lm-sys/FastChat)), [Firefly]([https://github.com/yangjianxin1/Firefly](https://github.com/yangjianxin1/Firefly)), [**LLaMA Efficient Tuning**]([https://github.com/hiyouga/LLaMA-Efficient-Tuning](https://github.com/hiyouga/LLaMA-Efficient-Tuning)), etc. We will soon update the relevant codes.
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 ## Tokenizer
 
diff --git a/FAQ_zh.md b/FAQ_zh.md
index 23205fd..de29bec 100644
--- a/FAQ_zh.md
+++ b/FAQ_zh.md
@@ -21,6 +21,8 @@ flash attention是一个用于加速模型训练推理的可选项，且仅适
 #### transformers_stream_generator/tiktoken/accelerate，这几个库提示找不到，怎么办？
 
 运行如下命令：`pip install -r requirements.txt`。相关依赖库在[https://github.com/QwenLM/Qwen-7B/blob/main/requirements.txt](https://github.com/QwenLM/Qwen-7B/blob/main/requirements.txt) 可以找到。
+<br><br>
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 ## Demo & 推理
 
@@ -59,6 +61,7 @@ Qwen当前支持流式推理。见位于`modeling_qwen.py`的`chat_stream`函数
 #### 处理长序列时效果有问题**
 
 请确认是否开启ntk。若要启用这些技巧，请将`config.json`里的`use_dynamc_ntk`和`use_logn_attn`设置为`true`。最新代码默认为`true`。
+<br><br>
 
 
 ## 微调
@@ -66,6 +69,7 @@ Qwen当前支持流式推理。见位于`modeling_qwen.py`的`chat_stream`函数
 #### 当前是否支持SFT和RLHF？
 
 我们目前未提供SFT和RLHF代码。当前有多个外部项目已实现支持，如[FastChat](**[https://github.com/lm-sys/FastChat](https://github.com/lm-sys/FastChat))、[Firefly]([https://github.com/yangjianxin1/Firefly](https://github.com/yangjianxin1/Firefly))、[**LLaMA Efficient Tuning**]([https://github.com/hiyouga/LLaMA-Efficient-Tuning](https://github.com/hiyouga/LLaMA-Efficient-Tuning))等。我们会尽快更新这部分代码和说明。
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 ## Tokenizer