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Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Right click on it and click on Extract Here\n[Hindi] इस पर राइट क्लिक करें और एक्सट्रैक्ट हियर पर क्लिक करें,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Water is generally used as a solvent.\n[Hindi] पानी का उपयोग आमतौर पर एक विलायक के रूप में किया जाता है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] So, we wish to print the squares of all the odd numbers below 10, which are not multiples of 3, we would modify the for loop as follows.\n[Hindi] इसलिए, हम 10 से नीचे के सभी विषम संख्याओं के वर्गों को प्रिंट करना चाहते हैं, जो 3 के गुणक नहीं हैं, हम निम्नलिखित रूप में फॉर लूप को संशोधित करेंगे।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] The sinking of the U.S. battleship Maine in Havana Harbor in 1898 was the immediate cause of the Spanish–American War.\n[Hindi] 1898 में अमरीका और स्पेनिश युद्ध के तुरंत कारण में अमरीका में अमरीका में अमरीका की लड़ाई की गिरावट हो गई।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] So merely seeing the program, you can understand only 1% of the programming benefits but to have the best skill, you definitely have to write the program and another suggestion is that while you are writing the program whatever you want to have certain modification do it and see whether it is working or not.\n[Hindi] तो केवल प्रोग्राम को देखते हुए, आप प्रोग्रामिंग लाभों का केवल 1% समझ सकते हैं लेकिन सबसे अच्छा कौशल रखने के लिए, आपको निश्चित रूप से प्रोग्राम लिखना होगा और एक और सुझाव यह है कि जब आप प्रोग्राम लिख रहे हैं तो आप जो भी चाहते हैं उसे कुछ संशोधन करें और देखें कि यह काम कर रहा है या नहीं।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] We can handle multiple exceptions using throws as shown here.\n[Hindi] जैसा कि यहां दिखाया गया है, हम थ्रो का उपयोग करके कई अपवादों को संभाल सकते हैं।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] To follow this tutorial, ensure that Joomla 3.4.1 is installed in your system.\n[Hindi] इस ट्यूटोरियल का पालन करने के लिए, यह सुनिश्चित करें कि आपके सिस्टम में जूमला 3.4.1 इंस्टॉल है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Now, here you see first we will check that whether stack is empty.\n[Hindi] अब, यहां आप पहले देखते हैं कि हम जांच करेंगे कि स्टैक खाली है या नहीं।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Now we will change the default Overview map with a different map.\n[Hindi] अब हम डिफ़ॉल्ट ओवरव्यू मैप को एक अलग मैप के साथ बदल देंगे।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Next, let's look at conversion of structured text to map. Here, we will condense long documents into a map without losing it’s structure.\n[Hindi] इसके बाद, संरचित पाठ को नक्शे में परिवर्तित करने पर ध्यान दें। यहां, हम लंबे दस्तावेजों को बिना इसकी संरचना को खोए एक नक्शे में संघनित करेंगे।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Watch the video available at following link. http://spoken-tutorial.org/\n[Hindi] वीडियो निम्नलिखित लिंक पर उपलब्ध हैः http:// spoken-tutorial. org /,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Use code from other languages in the cells.\n[Hindi] कक्षों में अन्य भाषाओं के कोड का उपयोग करें।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] As a programmer point of view you don’t have to bother anything about how they are taking there, but it is the different procedures, the different concept, the different mechanisms are used to facilitate the different way something is very fast, and something is not so accurate whatever it is there.\n[Hindi] एक प्रोग्रामर के दृष्टिकोण के रूप में आपको इस बारे में कुछ भी परेशान करने की आवश्यकता नहीं है कि वे वहां कैसे ले जा रहे हैं, लेकिन यह अलग-अलग प्रक्रियाएं हैं, अलग-अलग अवधारणा हैं, अलग-अलग तंत्रों का उपयोग अलग-अलग तरीके से सुविधा प्रदान करने के लिए किया जाता है-कुछ बहुत तेजी से है, और कुछ इतना सटीक नहीं है जो भी हो।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Next let us move on to Matrix Algebra.\n[Hindi] अब हम Matrix Algebra पर चलते हैं।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] The activity opens on the interface. Here we see the words grouped under different headings like action, adjective, color, number, etc. I will click on the action heading. Words used to describe action are grouped in this section.\n[Hindi] गतिविधि इंटरफेस पर खुलती है। यहां हम विभिन्न शीर्षकों जैसे कि क्रिया, विशेषण, रंग, संख्या आदि के तहत समूह देखते हैं। मैं कार्रवाई शीर्षक पर क्लिक करूंगा। कार्रवाई का वर्णन करने के लिए उपयोग किए जाने वाले शब्द इस खंड में हैं।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] His travel in the U.S. included giving talks on Ayurveda at medical schools such as UCLA, Harvard, and Johns Hopkins.\n[Hindi] संयुक्त राज्य अमेरिका में उनके यात्राओं ने यूएसए, यूएसए, यूएसए, यूएसए, यूएसए, यूएसएलए, और जॉनस हॉपकिन्स जैसे मेडिकल स्कूलों में बातचीत की पेशकश की।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] So, just to recapture three common reasons for dependency between classes is that an object is a parameter in a dependent class method, the second reason is that in a dependent class, an object of another class, which is the independent class, is used as a local variable, and the third reason is that an object of an independent class is returned as the result of some method.\n[Hindi] इसलिए, वर्गों के बीच निर्भरता के तीन सामान्य कारणों को फिर से प्राप्त करने के लिए यह है कि एक ऑब्जेक्ट (object) एक आश्रित वर्ग विधि में एक पैरामीटर (parameter) है, दूसरा कारण यह है कि एक आश्रित वर्ग में, एक अन्य वर्ग का एक ऑब्जेक्ट (object), जो स्वतंत्र वर्ग है, का उपयोग एक स्थानीय वेरिएबल (variable) के रूप में किया जाता है, और तीसरा कारण यह है कि किसी स्वतंत्र वर्ग का एक ऑब्जेक्ट (object) किसी विधि के परिणाम के रूप में वापस आ जाता है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] You have to create the map container and then apply the method and you can see the result, the getting the result is very simple just simply put system.out.println() and then whole the container can be printed a particular record can be printed whatever the way you can print you can see the result.\n[Hindi] आपको मैप कंटेनर बनाना होगा और फिर विधि को लागू करना होगा और आप परिणाम देख सकते हैं, परिणाम प्राप्त करना बहुत सरल है बस system. out. println () और फिर पूरे कंटेनर को एक विशेष रिकॉर्ड मुद्रित किया जा सकता है जिस तरह से आप परिणाम देख सकते हैं।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] So total memory that is in use in your program can be maintained by a list, as a singly linked list or double linked list depending on what direction or both way or one way.\n[Hindi] तो कुल मेमोरी जो आपके प्रोग्राम में उपयोग में है, को एक सूची द्वारा, एक एकल लिंक सूची या डबल लिंक सूची के रूप में बनाए रखा जा सकता है जो इस बात पर निर्भर करता है कि कौन सी दिशा या दोनों तरह से या एक तरह से।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Observe that earth rotates on its axis back and forth.\n[Hindi] गौर कीजिए कि पृथ्वी अपने अक्ष पर आगे-पीछे घूमती है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] To record this tutorial, I am using Ubuntu Linux version 16.04 OS Firefox web browser 69 Windows 10 OS Microsoft Edge 40 web browser Freeplane 1.7.10 A working internet connection to download Freeplane\n[Hindi] इस ट्यूटोरियल को रिकॉर्ड करने के लिए, मैं उबुन्टू लिनक्स संस्करण 16.04 ओएस फायरफॉक्स वेब ब्राउजर 69 विंडोज 10 ओएस माइक्रोसॉफ्ट एज 40 वेब ब्राउजर 1.7.10 फ्रीप्लेन डाउनलोड करने के लिए एक इंटरनेट कनेक्शन का उपयोग कर रहा हूं,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] So, tree concept will be discussed in this class later on but tree is a very concept.\n[Hindi] इसलिए, इस वर्ग में बाद में ट्री की अवधारणा पर चर्चा की जाएगी, लेकिन ट्री एक बहुत ही अवधारणा है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Here you can see the swap method with two parameters instead of single parameter that we have discussed in the last example, x and y, both are of same type, TT, that is why if X is one type and Y is another type, then if you write T and U or whatever it is there, so that is a concept that you have to think about.\n[Hindi] यहां आप एकल पैरामीटर के बजाय दो मापदंडों के साथ स्वैप विधि देख सकते हैं, जिसे हमने पिछले उदाहरण में चर्चा की है, x और y, दोनों एक ही प्रकार के हैं, TT, यही कारण है कि यदि X एक प्रकार है और Y एक अन्य प्रकार है, तो यदि आप T और U या जो कुछ भी लिखते हैं, तो यह एक अवधारणा है जिसके बारे में आपको सोचना होगा।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Java developer uses those legacy classes to build the new collection framework in fact so that is the class has its own important.\n[Hindi] जावा डेवलपर उन विरासत वर्गों का उपयोग नए संग्रह ढांचे का निर्माण करने के लिए करता है ताकि कक्षा का अपना महत्व हो।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] We have a list something like var underscore list= within square bracket 1 comma 1 point 2 comma then again within square bracket 1 comma 2 var underscore list\n[Hindi] हमारे पास var underscore list = within square bracket 1 comma 1 point 2 comma फिर square bracket 1 comma 2 var underscore list है,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] So this basically gives an idea about the time complexity this one, now log 2 n, you compare the searching algorithm that we have discussed when data is stored in an array using simple Linear Searching technique, It takes the order of ‘n’.\n[Hindi] तो यह मूल रूप से समय जटिलता के बारे में एक विचार देता है, अब लॉग 2 एन, आप खोज एल्गोरिथ्म की तुलना करते हैं जो हमने चर्चा की है जब डेटा को सरल लीनियर खोज तकनीक का उपयोग करके एक सरणी में संग्रहीत किया जाता है, यह 'एन' का क्रम लेता है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Click on the Color tab.\n[Hindi] कलर टैब पर क्लिक करें।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] So, this concept it is there, now, so, this is basically the links field that you have to maintained for a sparse representation of a matrix and then the data.\n[Hindi] तो, यह अवधारणा यह है, अब, इसलिए, यह मूल रूप से लिंक क्षेत्र है जिसे आपको एक मैट्रिक्स और फिर डेटा के विरल प्रतिनिधित्व के लिए बनाए रखना है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Notice the two column data format. First column is x data and second column is y data.\n[Hindi] दो कॉलम डेटा प्रारूप पर ध्यान दें। पहला कॉलम x डेटा है और दूसरा कॉलम y डेटा है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] You know exactly when a data type is called Enumerated, It is basically a Set of finite elements which is fixed.\n[Hindi] आप जानते हैं कि वास्तव में जब एक डेटा टाइप को गणना कहा जाता है, तो यह मूल रूप से परिमित तत्वों का एक सेट है जो तय किया जाता है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] I realize now that I had marked the wrong answer while creating this quiz.\n[Hindi] मुझे अब एहसास हुआ कि मैंने इस प्रश्नोत्तरी को बनाते समय गलत उत्तर चिह्नित किया था।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] In this tutorial, we learnt about different source types such as Internal Relay Output pin\n[Hindi] इस ट्यूटोरियल में, हमने विभिन्न स्रोत प्रकारों के बारे में सीखा जैसे कि आंतरिक रिले आउटपुट पिन,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] The inverse of a matrix A, A raise to minus one, is also called the reciprocal matrix, such that A multiplied by A inverse will give 1.\n[Hindi] एक मैट्रिक्स A का व्युत्क्रम, A से शून्य तक वृद्धि को पारस्परिक मैट्रिक्स भी कहा जाता है, जैसे कि A को A से गुणा करने पर 1 मिलेगा।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] List of National Highways in India (by Highway Number) List of National Highways in India National Highways Development Project National Highways Authority of India (NHAI) NH network map of India\n[Hindi] भारत में राष्ट्रीय हाईवे प्रोजेक्ट (NHAI) भारत के राष्ट्रीय हाईवे प्रोजेक्ट में राष्ट्रीय हाईवे प्रौद्योगिकी प्रौद्योगिकी प्रौद्योगिकी प्रौद्योगिकी के राष्ट्रीय हाईवे प्रौद्योगिकी प्रौद्योगिकी प्रौद्योगिकी प्रौद्योगिकी प्रौद्योगिकी प्रौद्योगिकी प्रौद्योगिकी प्रौद्योगिकी प्रौद्योगिकी प्रौद्योगिकी (NHAI) NH प्रौद्योगिकी प्रौद्योगिकी प्रौद्योगिकी प्रौद्योगिकी प्रौद्योगिकी प्रौद्योगिकी प्रौद्योगिकी प्रौद्योगिकी प्रौद्योगिकी,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] So, that it will print also, but it is not the good idea to how to print a particular object but this is a nice idea that how the using the print data method of objects itself and we can print it.\n[Hindi] इसलिए, यह प्रिंट भी करेगा, लेकिन किसी विशेष वस्तु को कैसे प्रिंट करना है यह अच्छा विचार नहीं है, लेकिन यह एक अच्छा विचार है कि वस्तुओं के प्रिंट डेटा विधि का उपयोग कैसे किया जाता है और हम इसे प्रिंट कर सकते हैं।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Especially popular were "Arithmetic for entertainment", "Mechanics for entertainment", "Geometry for Entertainment", "Astronomy for entertainment", "Lively Mathematics", " Physics Everywhere", and "Tricks and Amusements".\n[Hindi] विशेष रूप से लोकप्रिय थे "अनुवंशिक मनोरंजन", "अनुवंशिक तकनीक", "अनुवंशिक के लिए प्रौद्योगिकी", "अनुवंशिक के लिए प्रौद्योगिकी", "अनुवंशिक प्रौद्योगिकी", "अनुवंशिक प्रौद्योगिकी", "अनुवंशिक प्रौद्योगिकी" और "अनुवंशिक प्रौद्योगिकी"।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] I will tell you exactly what is the syntax that we can follow, this is the as usual same up to this one, MethodName and this can be a generic type or a specific type according to your own, it can be integer or it can be generic type.\n[Hindi] मैं आपको बताऊंगा कि वाक्यविन्यास क्या है जिसका हम अनुसरण कर सकते हैं, यह सामान्य रूप से एक ही है, मेथोडनेम और यह आपके स्वयं के अनुसार एक सामान्य प्रकार या एक विशिष्ट प्रकार हो सकता है, यह पूर्णांक हो सकता है या यह सामान्य प्रकार हो सकता है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] This is the deletion method, delete ‘int’ lock that mean we want to delete an element from the ‘l o c’ position and this is the usual code, that you can check it and this basically the after deletion the push up one location for all elements so that the vacant position can be filled.\n[Hindi] यह हटाने की विधि है, 'int' लॉक को हटाएं जिसका मतलब है कि हम 'l o c' स्थिति से एक तत्व को हटाना चाहते हैं और यह सामान्य कोड है, कि आप इसकी जांच कर सकते हैं और यह मूल रूप से सभी तत्वों के लिए एक स्थान को हटाने के बाद पुश अप करता है ताकि खाली स्थान भरा जा सके।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] This clicks and waits for the page to load.\n[Hindi] यह क्लिक करता है और पृष्ठ के लोड होने का इंतजार करता है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] So, inside the constructor, type: count++ semicolon.\n[Hindi] तो, कंस्ट्रक्टर के अंदर, टाइप करेंः count + + semicolon.,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] These are: int,float, complex\n[Hindi] ये हैंः int, float, complex,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Now, so, these are there are therefore all together six different ways.\n[Hindi] अब, इसलिए, ये सभी छह अलग-अलग तरीके हैं।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Click on the Half underscore adder and click on the OK button.\n[Hindi] हाफ स्कोर एडर पर क्लिक करें और ओके बटन पर क्लिक करें।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] The IUCN Red List of Threatened Species is the best-known worldwide conservation status listing and ranking system.\n[Hindi] यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय संघ के संयुक्त यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय यूरोपीय,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Now, if it is a large matrix and, many entries are null then there is a huge wastage of memory actually.\n[Hindi] अब, अगर यह एक बड़ा मैट्रिक्स है और, कई प्रविष्टियां शून्य हैं तो वास्तव में मेमोरी की बहुत बड़ी बर्बादी होती है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Now average search time means we can search an item in a binary search tree and it can be in any place in the tree, can be in root, can be in the leaf node, can be the inter node or whatever it is there.\n[Hindi] अब औसत खोज समय का मतलब है कि हम एक बाइनरी खोज ट्री (binary search tree) में एक आइटम की खोज कर सकते हैं और यह ट्री (tree) में किसी भी स्थान पर हो सकता है, रूट (root) में हो सकता है, लीफ नोड (leaf node) में हो सकता है, इंटर नोड (inter node) या जो कुछ भी हो सकता है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] you just simply use this method to solve your program which I will again give enough illustration and then demonstrate programming writing.\n[Hindi] आप बस अपने कार्यक्रम को हल करने के लिए इस विधि का उपयोग करें जिसे मैं फिर से पर्याप्त चित्रण दूंगा और फिर प्रोग्रामिंग लेखन का प्रदर्शन करूंगा।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] We will now see move and rotate tools.\n[Hindi] अब हम मूव और रोटेट टूल्स (move and rotate tools) देखेंगे।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] In this tutorial, we have learnt about: Form Input types: Date, Radio, Number, Form Elements: Select, Datalist, Fieldset, Form Methods: GET, POST in HTML\n[Hindi] इस ट्यूटोरियल में, हमने निम्नलिखित के बारे में सीखा हैः फॉर्म इनपुट प्रकारः तारीख, रेडियो, नंबर, फॉर्म एलिमेंटः सेलेक्ट, डेटालिस्ट, फील्ड सेट, फॉर्म मेथड्स: जीईटी, एचटीएमएल में पोस्ट,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] The idea is that you can maintain a package where your defined linked list structures and all methods in it can be there and you can import this package into your application program and then just simply call the different methods whenever it is required.\n[Hindi] विचार यह है कि आप एक पैकेज को बनाए रख सकते हैं जहां आपकी परिभाषित लिंक्ड लिस्ट संरचनाएं और इसमें सभी विधियां हो सकती हैं और आप इस पैकेज को अपने एप्लिकेशन प्रोग्राम में इम्पोर्ट कर सकते हैं और फिर जब भी आवश्यकता हो तो बस विभिन्न विधियों को कॉल कर सकते हैं।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Verify the custom exception class.\n[Hindi] कस्टम अपवाद वर्ग को सत्यापित करें.,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] We can do first is that 'ptr1's left link should be set by the new, so this basically address will be set as new, that means it points to this one and right link of this field will be set by 'ptr1'.\n[Hindi] हम पहले यह कर सकते हैं कि 'ptr1' का लेफ्ट लिंक नए द्वारा सेट किया जाना चाहिए, इसलिए यह मूल रूप से एड्रेस नया के रूप में सेट किया जाएगा, इसका मतलब है कि यह इस एक की ओर इंगित करता है और इस फील्ड का राइट लिंक 'ptr1' द्वारा सेट किया जाएगा।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] The File option allows you to read in existing proxy file settings.\n[Hindi] फ़ाइल विकल्प आपको मौजूदा प्रॉक्सी फ़ाइल सेटिंग्स में पढ़ने की अनुमति देता है.,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] So if it is any collection then you can convert this collection copy, this collection using only one statement that you can copy as list into arrays and then you can get the element and then array can be there, so, then you can use it.\n[Hindi] इसलिए यदि यह कोई संग्रह है तो आप इस संग्रह की प्रति को परिवर्तित कर सकते हैं, इस संग्रह को केवल एक बयान का उपयोग करके आप सूची के रूप में कॉपी कर सकते हैं और फिर आप तत्व प्राप्त कर सकते हैं और फिर सरणी हो सकती है, इसलिए आप इसका उपयोग कर सकते हैं।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Similarly, set the limits of y-axis in a similar manner.\n[Hindi] इसी तरह, y-अक्ष की सीमाओं को इसी तरह से सेट करें।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Hold the left mouse button and drag to draw a rectangle, as shown here.\n[Hindi] बायाँ माउस बटन पकड़ें और आयत खींचने के लिए खींचें, जैसा कि यहाँ दिखाया गया है.,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] By 1992, the ski jumping competitions were referred by their K-point distances rather than their run length prior to launching from the ski jump (90 meters for the normal hill and 120 meters for the large hill, respectively) and have been that way ever since.\n[Hindi] 1992 में, स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विच स्विचर्स स्विच स्विच,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] So, in particular if you go back to the binomial model you can actually see this P of s are going to be p and 1 - p and the return RIS, there are two possible values that the namely your u and d given by the upward and the downward movement.\n[Hindi] इसलिए, विशेष रूप से यदि आप द्विपद मॉडल (binomial model) पर वापस जाते हैं तो आप वास्तव में देख सकते हैं कि यह p और 1-p होने जा रहा है और रिटर्न RIS, दो संभावित मान हैं जो आपके u और d को ऊपर की ओर और नीचे की ओर देते हैं।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Now so Reader class it is very similar to ‘Input Stream’ class basically it basically read character by character and it has many methods those are basically useful for reading purpose only reading character by character ok, these are the different class we have already discussed about it is a basically listed in a tabular form you can check it ah but mainly we will discuss about\n[Hindi] अब तो रीडर क्लास यह मूल रूप से 'इनपुट स्ट्रीम' क्लास के समान है और इसके कई तरीके हैं जो मूल रूप से केवल चरित्र दर चरित्र पढ़ने के लिए उपयोगी हैं, ये अलग-अलग क्लास हैं जिनके बारे में हमने पहले ही चर्चा की है कि यह मूल रूप से एक सारणीबद्ध रूप में सूचीबद्ध है आप इसकी जांच कर सकते हैं लेकिन मुख्य रूप से हम इसके बारे में चर्चा करेंगे।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] We can also get the same output by typing, sorted inside brackets marks comma reverse equal to True\n[Hindi] हम कोष्ठक के अंदर टाइप करके भी वही आउटपुट प्राप्त कर सकते हैं, जो सत्य के बराबर कॉमा रिवर्स के बराबर है,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Let us check and resolve it.\n[Hindi] आइए हम इसकी जांच करें और इसका समाधान करें।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Now overall, the collection is as we told you that collection is a very vast thing, this is vast because it covers so many data structures in one bundle.\n[Hindi] अब कुल मिलाकर, संग्रह जैसा कि हमने आपको बताया कि संग्रह एक बहुत बड़ी बात है, यह विशाल है क्योंकि यह एक बंडल में कई डेटा संरचनाओं को कवर करता है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] For example, whenever you want to add it, so adding go on adding list in this direction, so basically when you go for enqueue, so it is basically enqueue is equivalent to insert at end, if end is the end of the list actually.\n[Hindi] उदाहरण के लिए, जब भी आप इसे जोड़ना चाहते हैं, तो इस दिशा में सूची जोड़ना जारी रखें, इसलिए मूल रूप से जब आप इनक्यू के लिए जाते हैं, तो यह मूल रूप से इनक्यू अंत में डालने के बराबर है, यदि अंत वास्तव में सूची का अंत है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] so we will get the answer as 1 by 2 into pi.\n[Hindi] तो हम 1 द्वारा 2 pi के रूप में जवाब मिल जाएगा।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] All these methods basically facilitate actions like creating a particular key, associating key value and the object, searching/adding/removing a particular object when it's key is given and a lot more.\n[Hindi] ये सभी तरीके मूल रूप से एक विशेष कुंजी बनाने, कुंजी मूल्य और वस्तु को जोड़ने, खोज/जोड़ने/हटाने जैसे कार्यों को सुविधाजनक बनाते हैं।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Click on Instructions and then Insert Contact.\n[Hindi] निर्देश पर क्लिक करें और फिर संपर्क डालें।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] But I want to see that not only learning the different data structures, but at the same time we will also learn the programming for all these data structures.\n[Hindi] लेकिन मैं देखना चाहता हूं कि न केवल विभिन्न डेटा संरचनाओं को सीखना है, बल्कि साथ ही हम इन सभी डेटा संरचनाओं के लिए प्रोग्रामिंग भी सीखेंगे।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] So we get similar plot but the only difference is the input widget.\n[Hindi] तो हमें समान प्लॉट मिलता है लेकिन अंतर केवल इनपुट विज़ेट है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Now our next step is basically to add different methods related to this kind of stack manipulation namely 'push()', 'pop()', 'isEmpty()' 'printStack()'.\n[Hindi] अब हमारा अगला कदम मूल रूप से 'पुश ()', 'पॉप ()', 'इसमम्प्टी ()' प्रिंटस्टैक () 'नामक इस तरह के स्टैक हेरफेर से संबंधित विभिन्न विधियों को जोड़ना है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] These short double-stranded fragments are called small interfering RNAs (siRNAs).\n[Hindi] ये छोटे-छोटे दो-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छोड़-छो-छोड़-छोड़-छो-छोड़-छो-छोड़-छो-छोड़-छोड़-छो-छो-छोड़-छो,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] We can see two links here.\n[Hindi] हम यहां दो लिंक देख सकते हैं।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Any node can store any values so in that sense you can store, but actually from the application point of view a node should not store the duplicate values, all nodes should be unique, because it does not have otherwise any meaningful application of it, actually.\n[Hindi] कोई भी नोड किसी भी वैल्यू (value) को स्टोर कर सकता है, इसलिए उस अर्थ में आप स्टोर कर सकते हैं, लेकिन वास्तव में एप्लीकेशन (application) के दृष्टिकोण से एक नोड को डुप्लिकेट वैल्यू (duplicate value) को स्टोर नहीं करना चाहिए, सभी नोड अद्वितीय होने चाहिए, क्योंकि वास्तव में इसका कोई सार्थक एप्लीकेशन (application) नहीं है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] The d e b file has been downloaded.\n[Hindi] डी ई बी फाइल डाउनलोड कर ली गई है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] This is how the CSS Box model looks like. Each layer has some properties of its own. Let us understand these one by one through examples.\n[Hindi] सीएसएस बॉक्स मॉडल इस तरह दिखता है। प्रत्येक परत के अपने कुछ गुण होते हैं। आइए हम उदाहरणों के माध्यम से एक-एक करके इन्हें समझते हैं।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Notice that the Gender field is displayed and it has three radio buttons.\n[Hindi] ध्यान दें कि लिंग क्षेत्र प्रदर्शित किया गया है और इसमें तीन रेडियो बटन हैं।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] If this function fails then the error will be returned.\n[Hindi] यदि यह फंक्शन विफल रहता है तो त्रुटि वापस कर दी जाएगी।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Similarly, when we instantiate the box with the new keyword, we get the object reference myBox which just points to the box object.\n[Hindi] इसी तरह, जब हम नए कीवर्ड के साथ बॉक्स को इंस्टैंट करते हैं, तो हमें ऑब्जेक्ट रेफरेंस myBox मिलता है जो सिर्फ बॉक्स ऑब्जेक्ट की ओर इशारा करता है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] 1.94 appears in C9.\n[Hindi] 1. 94 सी9 में दिखता है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] To practice this tutorial, the user should have Basic knowledge of Linux terminal commands, Experience with simulating cases in OpenFOAM, Working skills in ParaView.\n[Hindi] इस ट्यूटोरियल का अभ्यास करने के लिए, उपयोगकर्ता को लिनक्स टर्मिनल कमांड्स का बुनियादी ज्ञान, ओपनएफओएएम में सिमुलेशन मामलों का अनुभव, पैराव्यू में कार्य कौशल होना चाहिए।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Write code for gcd and write tests for it\n[Hindi] जीसीडी के लिए कोड लिखें और इसके लिए परीक्षण लिखें,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Rename the Coil as ‘heat’ and configure it as SET-only Coil.\n[Hindi] कॉइल को 'हीट' के रूप में पुनः नामकरण करें और इसे SET-only Coil के रूप में कॉन्फ़िगर करें।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Click on Ok to download the file.\n[Hindi] फाइल डाउनलोड करने के लिए ओके पर क्लिक करें।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Likewise, we can insert any text or callout in our drawing, as per our requirements.\n[Hindi] इसी तरह, हम अपनी आवश्यकताओं के अनुसार, अपनी ड्राइंग में कोई भी टेक्स्ट या कॉलआउट डाल सकते हैं।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] So if we do it our task will be complete, so let us see we can add the method one by one.\n[Hindi] तो अगर हम इसे करते हैं तो हमारा काम पूरा हो जाएगा, तो हम देखते हैं कि हम एक-एक करके विधि जोड़ सकते हैं।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Here, as we have extended the Human class with Animal, so Animal is the parent class.\n[Hindi] यहां, जैसा कि हमने पशु के साथ मानव वर्ग का विस्तार किया है, इसलिए पशु अभिभावक वर्ग है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] As the name Tree implies that a Tree basically is a real life Tree, a Tree has a root and then it has many branches and then finally it has leaf and then fruits, flower and everything is there.\n[Hindi] जैसा कि नाम ट्री से पता चलता है कि एक ट्री मूल रूप से एक वास्तविक जीवन ट्री है, एक ट्री की एक जड़ होती है और फिर इसकी कई शाखाएं होती हैं और फिर अंत में इसमें पत्ती होती है और फिर फल, फूल और सब कुछ होता है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Glue points are not the same as handles We use handles to resize an object Whereas glue points are used to glue a connector to an object\n[Hindi] गोंद बिंदु हैंडल के समान नहीं होते हैं हम किसी वस्तु का आकार बदलने के लिए हैंडल का उपयोग करते हैं जबकि गोंद बिंदुओं का उपयोग किसी वस्तु से कनेक्टर को गोंद लगाने के लिए किया जाता है,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] So a series of number can be called in a Fibonacci sequence, if they satisfy certain property, the property is that the last elements or the any 'i'th element is the sum of the previous two elements , if it follows this property then a sequence of numbers will be called a Fibonacci sequence.\n[Hindi] तो एक फिबोनाची अनुक्रम में संख्या की एक श्रृंखला को कहा जा सकता है, यदि वे कुछ संपत्ति को संतुष्ट करते हैं, तो संपत्ति यह है कि अंतिम तत्व या कोई भी 'i' th तत्व पिछले दो तत्वों का योग है, यदि यह इस संपत्ति का अनुसरण करता है तो संख्याओं का एक अनुक्रम फिबोनाची अनुक्रम कहा जाएगा।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Generally links are present as menus in web pages. Usually the menus are not underlined. So we will use text decoration property to remove the underline.\n[Hindi] आम तौर पर लिंक वेब पृष्ठों में मेनू के रूप में मौजूद होते हैं। आमतौर पर मेनू रेखांकित नहीं होते हैं। इसलिए हम अंडरलाइन को हटाने के लिए पाठ सजावट गुण का उपयोग करेंगे।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Count up which is represented as CTU.\n[Hindi] गणना करें जिसे सीटीयू के रूप में दर्शाया गया है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Read the information given about Nearest neighbour analysis on the right-panel.\n[Hindi] दाहिने पैनल पर नजदीकी पड़ोसी विश्लेषण के बारे में दी गई जानकारी पढ़ें।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Verified Kepler's second law using Kepler's second law simulation.\n[Hindi] केपलर के दूसरे नियम सिमुलेशन का उपयोग करते हुए सत्यापित केपलर का दूसरा नियम।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] We see that it raises a NameError saying that the name 'linspace' is not defined.\n[Hindi] हम देखते हैं कि यह एक नाम त्रुटि उठाता है जिसमें कहा गया है कि 'लाइनस्पेस' नाम परिभाषित नहीं है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Type k is equal to inside square brackets one comma two comma one comma three and press Enter Then type k dot remove inside parentheses k inside square brackets two and press Enter Type k and press Enter We can see the output as [2,1,3]. Since it deletes the first occurrence of what is returned by k inside square brackets two which is one.\n[Hindi] टाइप "k" "वर्ग कोष्ठकों के अंदर के के बराबर है एक अल्पविराम दो अल्पविराम एक अल्पविराम तीन और" "Enter" "दबाएं फिर टाइप करें" "k" "डॉट हटाएं कोष्ठक के अंदर के वर्ग कोष्ठक के अंदर दो और" "Enter Type k" "दबाएं" "हम आउटपुट [2,1,3] के रूप में देख सकते हैं। चूंकि यह वर्ग कोष्ठक के अंदर के द्वारा वापस की गई पहली घटना को मिटाता है दो जो एक है।",\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] Value for dspace.dir is C:/dspace\n[Hindi] dspace. dir का मान है C:/dspace,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] For some events in a state, it produces a transition, let say event1 in the state1 causes a transition to state2, then we write here as the event1 occurs in state1, the system transmits to state2 (state = state2).\n[Hindi] किसी राज्य में कुछ घटनाओं के लिए, यह एक संक्रमण का उत्पादन करता है, मान लीजिए कि राज्य 1 में घटना 1 राज्य 2 में संक्रमण का कारण बनती है, फिर हम यहां लिखते हैं कि घटना 1 राज्य 1 में होती है, सिस्टम राज्य 2 (राज्य = राज्य 2) में स्थानांतरित होता है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] I mean official websites this link it is there and this book also I should suggest you to go through, so that you can study much more programs that we have discussed about in an internet intermittently you can use for any type of class and you can create it and I have given as an illustration only for few 3, 4 objects instead you can add few more objects into them very large set of objects and even you can create a set of objects as an array list or some vector also to store the table into this one, how it can be done this left as an exercise for you.\n[Hindi] मेरा मतलब है कि आधिकारिक वेबसाइटों का यह लिंक है और इस पुस्तक को भी मुझे आपको इसके माध्यम से जाने का सुझाव देना चाहिए, ताकि आप उन अधिक कार्यक्रमों का अध्ययन कर सकें, जिनके बारे में हमने इंटरनेट में चर्चा की है कि आप किसी भी प्रकार के वर्ग के लिए उपयोग कर सकते हैं और आप इसे बना सकते हैं और मैंने केवल कुछ 3,4 वस्तुओं के लिए एक चित्रण के रूप में दिया है इसके बजाय आप उनमें वस्तुओं के बहुत बड़े सेट को जोड़ सकते हैं और यहां तक कि आप इसमें तालिका को स्टोर करने के लिए वस्तुओं का एक सेट या कुछ वेक्टर भी बना सकते हैं, इसे आपके लिए एक अभ्यास के रूप में कैसे छोड़ा जा सकता है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] So, there is a java programming features because array is a simple, a very effective one data structure, no any program language can think about without an array in it.\n[Hindi] तो, एक जावा प्रोग्रामिंग विशेषताएं हैं क्योंकि सरणी एक सरल, बहुत प्रभावी डेटा संरचना है, कोई भी प्रोग्राम भाषा इसमें सरणी के बिना नहीं सोच सकती है।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] South Dakota is bordered by the states of North Dakota (to the north), Minnesota (to the east), Iowa (to the southeast), Nebraska (to the south), Wyoming (to the west), and Montana (to the northwest).\n[Hindi] दक्षिण डोकोका उत्तर डोकोका राज्यों द्वारा सीमित है (उत्तर डोकोका), मिनोटाना (उत्तर के लिए), ओवियो (उत्तर के लिए), नब्रासा (उत्तर के लिए), Wyoming (उत्तर के लिए), और म Montana (उत्तर के लिए)।,\npredict the DA-score. | DA-score: | qe |
Context: A quality estimation model predicts the DA score on a scale of 0 to 100. Be precise and penalize DA score based on errors in the Hindi sentence. Do not consider any other existing translation evaluation metrics. \n\nTask: For the following translation from English to Hindi,\n[English] But when we insert a new node 2 then we can check the change of balance factor where these nodes has not change the balance factor but if you see here the nodes change their balance factor and we see that this node and this node become the culprit node.\n[Hindi] लेकिन जब हम एक नया नोड 2 डालते हैं तो हम संतुलन कारक के परिवर्तन की जांच कर सकते हैं जहां इन नोड्स ने संतुलन कारक को नहीं बदला है लेकिन यदि आप यहां देखते हैं तो नोड्स अपना संतुलन कारक बदलते हैं और हम देखते हैं कि यह नोड और यह नोड दोषी नोड बन जाता है।,\npredict the DA-score. | DA-score: | qe |