diff --git a/subtitles/zh-CN/02_the-carbon-footprint-of-transformers.srt b/subtitles/zh-CN/02_the-carbon-footprint-of-transformers.srt
index 9d2211f64..8c0b66d09 100644
--- a/subtitles/zh-CN/02_the-carbon-footprint-of-transformers.srt
+++ b/subtitles/zh-CN/02_the-carbon-footprint-of-transformers.srt
@@ -1,21 +1,21 @@
 1
 00:00:05,580 --> 00:00:08,820
-- 让我们谈谈变压器的碳足迹。
+- 让我们谈谈 transformer 的碳足迹。
 - So let's talk about the carbon footprint of transformers.
 
 2
 00:00:08,820 --> 00:00:10,530
-也许你看过这样的头条新闻
+也许您看过这样的头条新闻
 Maybe you've seen headlines such as this one
 
 3
 00:00:10,530 --> 00:00:13,530
-训练单个 AI 模型可以排放尽可能多的碳
+训练单个 AI 模型排放的碳含量
 that training a single AI model can emit as much carbon
 
 4
 00:00:13,530 --> 00:00:16,020
-作为他们一生中的五辆汽车。
+相当于五辆汽车生命周期的总排放量。
 as five cars in their lifetimes.
 
 5
@@ -25,122 +25,122 @@ So when is this true and is it always true?
 
 6
 00:00:19,440 --> 00:00:21,803
-好吧，这实际上取决于几件事。
+其实呢，这实际上取决于几个因素。
 Well, it actually depends on several things.
 
 7
 00:00:21,803 --> 00:00:23,430
-最重要的是，这取决于
+最重要的一点，这取决于
 Most importantly, it depends
 
 8
 00:00:23,430 --> 00:00:24,960
-关于你使用的能源类型。
+您所使用的能源类型。
 on the type of energy you're using.
 
 9
 00:00:24,960 --> 00:00:26,267
-如果你使用的是可再生能源，例如
+如果您使用的是可再生能源，例如
 If you're using renewable energy such as
 
 10
 00:00:26,267 --> 00:00:30,670
-太阳能、风能、水力发电，你真的
+太阳能、风能、水力发电，那么
 solar, wind, hydroelectricity, you're really
 
 11
 00:00:30,670 --> 00:00:33,810
-根本不排放任何碳，非常非常少。
+根本不会排放任何碳，非常非常少。
 not emitting any carbon at all, very, very little.
 
 12
 00:00:33,810 --> 00:00:36,769
-如果你使用的是煤炭等不可再生能源
+如果您使用的是煤炭等不可再生能源
 If you're using non-renewable energy sources such as coal
 
 13
 00:00:36,769 --> 00:00:39,570
-那么他们的碳足迹要高得多
+那么它们的碳足迹要高得多
 then their carbon footprint is a lot higher
 
 14
 00:00:39,570 --> 00:00:43,260
-因为本质上你正在排放大量的温室气体。
+因为本质上您正在排放大量的温室气体。
 'cuz essentially you are emitting a lot of greenhouse gases.
 
 15
 00:00:43,260 --> 00:00:44,670
-另一个方面是训练时间。
+另一个因素是训练时间。
 Another aspect is training time.
 
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 00:00:44,670 --> 00:00:47,232
-所以你训练的时间越长，消耗的能量就越多
+所以您训练的时间越长，消耗的能量就越多
 So the longer you train, the more energy you use
 
 17
 00:00:47,232 --> 00:00:50,250
-你使用的能源越多，你排放的碳就越多，对吗？
+您使用的能源越多，您排放的碳就越多，对吗？
 the more energy you use, the more carbon you emit, right?
 
 18
 00:00:50,250 --> 00:00:51,270
-所以这真的加起来
+所以所有这些因素一起进行考虑
 So this really adds up
 
 19
 00:00:51,270 --> 00:00:53,520
-特别是如果你正在训练大型模型
+特别是如果您正在训练大型模型
 especially if you're training large models for
 
 20
 00:00:53,520 --> 00:00:56,460
-数小时、数天和数周。
+且持续了数小时、数天或数周的时间。
 for hours and days and weeks.
 
 21
 00:00:56,460 --> 00:00:58,380
-你使用的硬件也很重要
+您使用的硬件也很重要
 The hardware you use also matters
 
 22
 00:00:58,380 --> 00:01:00,930
-因为例如某些 GPU 效率更高
+例如某些 GPU 效率更高
 because some GPUs, for example, are more efficient
 
 23
 00:01:00,930 --> 00:01:05,460
-比其他人和利用效率使用得当。
+相比较别的硬件来说，其利用效率使用得当。
 than others and utilizing efficiency use properly.
 
 24
 00:01:05,460 --> 00:01:07,500
-所以一直百分百地使用它们
+一直能够百分百地被使用
 So using them a hundred percent all the time
 
 25
 00:01:07,500 --> 00:01:10,650
-可以真正减少你的能源消耗。
+可以真正减少您的能源消耗。
 can really reduce the energy consumption that you have.
 
 26
 00:01:10,650 --> 00:01:13,290
-然后再次减少你的碳足迹。
+进一步减少您的碳足迹。
 And then once again, reduce your carbon footprint.
 
 27
 00:01:13,290 --> 00:01:15,870
-还有其他方面比如 IO
+还有其他因素比如 IO
 There's also other aspects such as IO
 
 28
 00:01:15,870 --> 00:01:17,730
-比如数据，等等，等等。
+比如数据，等等。
 such as data, et cetera, et cetera.
 
 29
 00:01:17,730 --> 00:01:20,940
-但这些是你应该关注的主要三个。
+但这三点是您应该关注的主要因素。
 But these are the main three that you should focus on.
 
 30
@@ -155,17 +155,17 @@ what does that really mean?
 
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 00:01:24,420 --> 00:01:27,480
-所以如果你看屏幕顶部
+所以如果您看屏幕顶部
 So if you look at the top of the screen
 
 33
 00:01:27,480 --> 00:01:30,480
-你有碳足迹
+您可以看到印度孟买的云计算实例
 you have a carbon footprint
 
 34
 00:01:30,480 --> 00:01:33,860
-印度孟买的云计算实例
+所产生的碳足迹
 of a cloud computing instance in Mumbai, India
 
 35
@@ -175,7 +175,7 @@ which emits 920 grams of CO2 per kilowatt hour.
 
 36
 00:01:38,700 --> 00:01:40,110
-这差不多一公斤
+这差不多有一公斤
 This is almost one kilogram
 
 37
@@ -185,17 +185,17 @@ of CO2 per kilowatt hour of electricity used.
 
 38
 00:01:43,680 --> 00:01:45,150
-如果你把它与加拿大相比，蒙特利尔
+如果您把它与加拿大蒙特利尔，
 If you compare that with Canada, Montreal
 
 39
 00:01:45,150 --> 00:01:48,720
-我现在所在的位置，每千克小时排放 20 克二氧化碳。
+也就是我现在所在的位置相比，每千克小时排放 20 克二氧化碳。
 where I am right now, 20 grams of CO2 per kilo hour.
 
 40
 00:01:48,720 --> 00:01:50,040
-所以这是一个非常非常大的区别。
+所以它们有着非常大的区别。
 So that's a really, really big difference.
 
 41
@@ -210,27 +210,27 @@ in Mumbai versus Montreal.
 
 43
 00:01:55,950 --> 00:01:57,720
-所以这真的可以加起来。
+所以这真的都需要考虑进去。
 And so this can really, really add up.
 
 44
 00:01:57,720 --> 00:01:59,820
-例如，如果你要训练一个模型数周
+例如，如果您要训练一个模型数周
 If you're training a model for weeks, for example
 
 45
 00:01:59,820 --> 00:02:01,920
-你乘以 40
+您乘以 40
 you're multiplying times 40
 
 46
 00:02:01,920 --> 00:02:03,450
-你排放的碳。
+您排放的碳。
 the carbon that you're emitting.
 
 47
 00:02:03,450 --> 00:02:05,070
-所以选择合适的实例
+因此选择合适的实例
 So choosing the right instance
 
 48
@@ -240,22 +240,22 @@ choosing a low carbon compute instance
 
 49
 00:02:07,080 --> 00:02:09,690
-这真的是你能做的最有影响力的事情。
+这真的是您能做的最有影响力的事情。
 is really the most impactful thing that you can do.
 
 50
 00:02:09,690 --> 00:02:13,020
-这就是它真正可以加起来的地方
+这就是它真正可以产生影响的地方
 And this is where it can really add up
 
 51
 00:02:13,020 --> 00:02:15,930
-如果你正在接受非常密集的训练
+如果您正在一个碳密集的地区
 if you're training in a very intensive
 
 52
 00:02:15,930 --> 00:02:17,580
-在一个非常碳密集的地区
+进行非常密集的训练
 in a very carbon intensive region
 
 53
@@ -275,27 +275,27 @@ that's the machine learning equivalent of recycling.
 
 56
 00:02:25,590 --> 00:02:28,292
-当你有可用的预训练模型时
+当您有可用的预训练模型时
 When you have pre-trained models available using them
 
 57
 00:02:28,292 --> 00:02:30,120
-你根本没有排放任何碳，对吧？
+您根本没有排放任何碳，对吧？
 you're not emitting any carbon at all, right?
 
 58
 00:02:30,120 --> 00:02:31,230
-你没有再训练任何东西。
+因为您没有在训练任何东西。
 You're not retraining anything.
 
 59
 00:02:31,230 --> 00:02:33,450
-所以这也在做你的功课
+因此先看看当前已经有了哪些工具
 So that's also doing your homework
 
 60
 00:02:33,450 --> 00:02:35,574
-并环顾四周已经存在的东西。
+能够帮助您处理所需要进行的任务。
 and kind of looking around what already exists.
 
 61
@@ -310,7 +310,7 @@ So once again
 
 63
 00:02:38,723 --> 00:02:40,590
-如果你找到几乎是你需要的模型
+如果您找到几乎是您需要的模型
 if you find a model that is almost what you need
 
 64
@@ -320,17 +320,17 @@ but not quite fine tuning the last couple of layers
 
 65
 00:02:43,530 --> 00:02:45,210
-让它真正适合你的目的
+通过调整来达到目的
 making it really fit your purpose instead
 
 66
 00:02:45,210 --> 00:02:46,500
-培训大型变压器
+而不是从头通过训练 transformer
 of training a large transformer
 
 67
 00:02:46,500 --> 00:02:48,810
-从头开始真的很有帮助，
+这样的话会大大提高您的效率
 from scratch can really help,
 
 68
@@ -340,7 +340,7 @@ starting with smaller experiments
 
 69
 00:02:51,270 --> 00:02:52,800
-并边调试边调试。
+并边调试边工作。
 and debugging as you go.
 
 70
@@ -350,17 +350,17 @@ So that means, for example, training
 
 71
 00:02:54,630 --> 00:02:58,770
-弄清楚数据编码，弄清楚，你知道
+弄清楚数据编码
 figuring out data encoding, figuring out, you know
 
 72
 00:02:58,770 --> 00:03:01,170
-确保没有小错误，你会
+确保没有小错误
 making sure that there's no small bugs, that you'll
 
 73
 00:03:01,170 --> 00:03:03,840
-你会意识到，你知道，经过 16 个小时的训练
+您会意识到，经过 16 个小时的训练
 you'll realize, you know, 16 hours into training
 
 74
@@ -370,12 +370,12 @@ starting small and really making sure
 
 75
 00:03:05,820 --> 00:03:08,760
-你在做什么，你的代码是什么，是稳定的。
+您在做什么，您的代码是什么，这样才是稳妥的。
 that what you're doing, what your code is, is stable.
 
 76
 00:03:08,760 --> 00:03:11,430
-然后最后做一个文献综述
+最后做一个文献综述
 And then finally doing a literature review to
 
 77
@@ -395,22 +395,22 @@ So random searches for hyper parameters
 
 80
 00:03:18,420 --> 00:03:21,300
-组合实际上被证明是有效的
+在寻找最佳配置作为网格搜索时
 combinations have actually shown to be as efficient
 
 81
 00:03:21,300 --> 00:03:24,000
-在寻找最佳配置作为网格搜索时。
+组合实际上被证明是有效的。
 in finding the optimal configuration as grid search.
 
 82
 00:03:24,000 --> 00:03:27,510
-但显然你并没有尝试所有可能的组合
+但显然您并没有尝试所有可能的组合
 But obviously you're not trying all possible combinations
 
 83
 00:03:27,510 --> 00:03:29,520
-你只是在尝试其中的一部分。
+您只是在尝试其中的一部分。
 you're only trying a subset of them.
 
 84
@@ -430,17 +430,17 @@ to the original paper by Strubell et all in 2019
 
 87
 00:03:36,300 --> 00:03:39,180
-臭名昭著的五辆车在他们一生的论文中。
+关于那五辆车的论文中。
 the infamous five cars in their lifetimes paper.
 
 88
 00:03:39,180 --> 00:03:40,013
-如果你只是看
+如果您只是考虑
 If you just look
 
 89
 00:03:40,013 --> 00:03:43,606
-在一个 2 亿周边变压器的变压器处
+一个 2 亿周边 transformer 的因素
 at a transformer of 200 million perimeter transformer
 
 90
@@ -450,7 +450,7 @@ it is carbon footprint is around 200 pounds of CO2
 
 91
 00:03:46,950 --> 00:03:47,940
-这很重要
+这很多
 which is significant
 
 92
@@ -465,22 +465,22 @@ It's not even a transatlantic flight.
 
 94
 00:03:52,893 --> 00:03:55,020
-它真正加起来的方式是当你在做的时候
+它真正到达这一量级的方式是当您在做
 How it really adds up is when you're doing
 
 95
 00:03:55,020 --> 00:03:56,190
-神经架构搜索
+神经架构搜索的时候
 neural architecture search
 
 96
 00:03:56,190 --> 00:03:58,560
-当你进行超参数调整时，以及
+当您进行超参数调整时，以及
 when you're doing hyper parameter tuning, and
 
 97
 00:03:58,560 --> 00:04:00,930
-这是在尝试所有可能的组合
+在尝试所有可能的组合的时候
 this is trying all possible combinations
 
 98
@@ -490,27 +490,27 @@ et cetera, et cetera.
 
 99
 00:04:01,763 --> 00:04:02,596
-这是哪里
+这是就像
 And this is where
 
 100
 00:04:02,596 --> 00:04:05,400
-就像来自 600,000 磅的二氧化碳一样。
+就像 600,000 磅的二氧化碳来自哪里一样。
 like the 600,000 pounds of CO2 came from.
 
 101
 00:04:05,400 --> 00:04:08,490
-所以这真的是事情加起来的地方。
+所以这真的是需要把所有因素考虑进来才可以。
 So this is really where things add up.
 
 102
 00:04:08,490 --> 00:04:11,880
-所以，但如果你正念认真地做事
+所以，但如果您正认真地做事
 So, but if you're doing things mindfully and conscientiously
 
 103
 00:04:11,880 --> 00:04:16,410
-那么你的碳足迹就不会那么大，
+那么您的碳足迹就不会那么大，
 then your carbon footprint wont be as big as,
 
 104
@@ -520,7 +520,7 @@ as the paper implied, some tools to figure
 
 105
 00:04:20,040 --> 00:04:22,111
-计算出你排放的 CO2 量。
+出您排放的 CO2 量。
 out how much CO2 exactly you're emitting.
 
 106
@@ -530,17 +530,17 @@ There's a web-based tool called machine
 
 107
 00:04:24,270 --> 00:04:26,430
-学习提交计算器，它可以让你
+学习提交计算器，它可以让您
 learning submissions calculator, which allows you
 
 108
 00:04:26,430 --> 00:04:29,010
-手动输入，例如，你使用的硬件
+手动输入，例如，您使用的硬件
 to manually input, for example, which hardware you used
 
 109
 00:04:29,010 --> 00:04:30,488
-你用了多少小时
+您用了多少小时
 how many hours you used it for
 
 110
@@ -550,12 +550,12 @@ where it was located locally or in the cloud.
 
 111
 00:04:34,260 --> 00:04:35,640
-然后它会给你一个估计
+然后它会给您一个估计
 And then it's gonna give you an estimate
 
 112
 00:04:35,640 --> 00:04:37,560
-你排放了多少二氧化碳。
+您排放了多少二氧化碳。
 of how much CO2 you emitted.
 
 113
@@ -570,27 +570,27 @@ is called code carbon.
 
 115
 00:04:41,190 --> 00:04:45,112
-所以你可以 PIP 安装它，你可以，你可以去 GitHub
+您可以 PIP 安装它，您可以去 GitHub
 So you can PIP install it, you can, you can go to the GitHub
 
 116
 00:04:45,112 --> 00:04:48,120
-本质上它与你的代码并行运行。
+它与您的代码并行运行。
 and essentially it runs in parallel to your code.
 
 117
 00:04:48,120 --> 00:04:49,085
-所以基本上你称之为
+所以基本上您调用它
 So essentially you call it
 
 118
 00:04:49,085 --> 00:04:51,060
-然后你做所有的训练。
+然后交给它做所有的训练。
 and then you do all your training.
 
 119
 00:04:51,060 --> 00:04:53,760
-然后最后它会给你一个估计
+最后它会给您一个估计
 And then at the end it's gonna give you an estimate
 
 120
@@ -600,12 +600,12 @@ a CSV file with an estimate of your emissions.
 
 121
 00:04:57,210 --> 00:04:59,250
-它会给你一些比较。
+它会给您一些比较。
 And it's gonna give you some comparisons.
 
 122
 00:04:59,250 --> 00:05:01,230
-它有一个可视化用户界面，你可以在其中真正看到
+它有一个可视化用户界面，您可以在其中真正看到
 It's got a visual UI where you can really look
 
 123
@@ -615,31 +615,31 @@ at how this compares to driving a car or watching TV.
 
 124
 00:05:04,680 --> 00:05:06,060
-所以它可以给你一个想法
+所以它可以给您一个想法
 So it can give you an idea
 
 125
 00:05:06,060 --> 00:05:07,740
-你的排放范围也是如此。
+您的排放范围也是如此。
 of the scope of your emissions as well.
 
 126
 00:05:07,740 --> 00:05:09,930
-实际上，code carbon 已经集成到汽车中
+实际上，code carbon 已经集成到 auto
 And actually, code carbon is already integrated into auto
 
 127
 00:05:09,930 --> 00:05:12,270
-和 LP，希望人们会使用它
+和 LP 中，希望人们能够
 and LP and hopefully people will be using it
 
 128
 00:05:12,270 --> 00:05:15,240
-开箱即用，轻松跟踪所有排放
+开箱即用，轻松跟踪所有训练和部署 transformer
 out of the box and easily tracking their emissions all
 
 129
 00:05:15,240 --> 00:05:17,523
-通过培训和部署变压器。
+的碳排放。
 through training and deploying transformers.