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data/clustering_individual-b9229914-47bc-4da8-a21b-89329fff8207.jsonl
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{"tstamp": 1722305188.8759, "task_type": "clustering", "type": "chat", "model": "sentence-transformers/all-MiniLM-L6-v2", "gen_params": {}, "start": 1722305188.8027, "finish": 1722305188.8759, "ip": "", "conv_id": "99f802e985564f459a4c8f1d35672366", "model_name": "sentence-transformers/all-MiniLM-L6-v2", "prompt": ["pyramidal", "motor", "Purkinje", "interneuron", "O", "B", "composite", "cinder cone", "flashlight", "sleeping bag", "whiskey", "tequila", "B12", "K", "B1", "sautéing", "grilling", "baking", "frying", "steaming"], "ncluster": 2, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
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{"tstamp": 1722305193.6001, "task_type": "clustering", "type": "chat", "model": "intfloat/multilingual-e5-large-instruct", "gen_params": {}, "start": 1722305193.4617, "finish": 1722305193.6001, "ip": "", "conv_id": "435492f9510842b3b662664dab56845d", "model_name": "intfloat/multilingual-e5-large-instruct", "prompt": ["fascism", "conservatism", "socialism", "hindsight bias", "dunning-kruger effect", "availability bias", "shovel", "wheelbarrow", "watering can", "pruning shears", "rake", "hoe", "trowel", "canine", "molar", "premolar", "incisor", "water filter", "tent", "camping stove", "sleeping bag", "backpack", "compass"], "ncluster": 5, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
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{"tstamp": 1722305193.6001, "task_type": "clustering", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1722305193.4617, "finish": 1722305193.6001, "ip": "", "conv_id": "8d6cf721df4a4d5ebea51d7bb875effb", "model_name": "Salesforce/SFR-Embedding-2_R", "prompt": ["fascism", "conservatism", "socialism", "hindsight bias", "dunning-kruger effect", "availability bias", "shovel", "wheelbarrow", "watering can", "pruning shears", "rake", "hoe", "trowel", "canine", "molar", "premolar", "incisor", "water filter", "tent", "camping stove", "sleeping bag", "backpack", "compass"], "ncluster": 5, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
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{"tstamp": 1722305188.8759, "task_type": "clustering", "type": "chat", "model": "sentence-transformers/all-MiniLM-L6-v2", "gen_params": {}, "start": 1722305188.8027, "finish": 1722305188.8759, "ip": "", "conv_id": "99f802e985564f459a4c8f1d35672366", "model_name": "sentence-transformers/all-MiniLM-L6-v2", "prompt": ["pyramidal", "motor", "Purkinje", "interneuron", "O", "B", "composite", "cinder cone", "flashlight", "sleeping bag", "whiskey", "tequila", "B12", "K", "B1", "sautéing", "grilling", "baking", "frying", "steaming"], "ncluster": 2, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
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{"tstamp": 1722305193.6001, "task_type": "clustering", "type": "chat", "model": "intfloat/multilingual-e5-large-instruct", "gen_params": {}, "start": 1722305193.4617, "finish": 1722305193.6001, "ip": "", "conv_id": "435492f9510842b3b662664dab56845d", "model_name": "intfloat/multilingual-e5-large-instruct", "prompt": ["fascism", "conservatism", "socialism", "hindsight bias", "dunning-kruger effect", "availability bias", "shovel", "wheelbarrow", "watering can", "pruning shears", "rake", "hoe", "trowel", "canine", "molar", "premolar", "incisor", "water filter", "tent", "camping stove", "sleeping bag", "backpack", "compass"], "ncluster": 5, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
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{"tstamp": 1722305193.6001, "task_type": "clustering", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1722305193.4617, "finish": 1722305193.6001, "ip": "", "conv_id": "8d6cf721df4a4d5ebea51d7bb875effb", "model_name": "Salesforce/SFR-Embedding-2_R", "prompt": ["fascism", "conservatism", "socialism", "hindsight bias", "dunning-kruger effect", "availability bias", "shovel", "wheelbarrow", "watering can", "pruning shears", "rake", "hoe", "trowel", "canine", "molar", "premolar", "incisor", "water filter", "tent", "camping stove", "sleeping bag", "backpack", "compass"], "ncluster": 5, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
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{"tstamp": 1722305501.7902, "task_type": "clustering", "type": "chat", "model": "intfloat/multilingual-e5-large-instruct", "gen_params": {}, "start": 1722305501.567, "finish": 1722305501.7902, "ip": "", "conv_id": "90f3e443c24747bf937dc778bac550b7", "model_name": "intfloat/multilingual-e5-large-instruct", "prompt": ["rock", "jazz", "classical", "flute", "guitar", "saxophone", "violin", "trumpet", "drums"], "ncluster": 2, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
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{"tstamp": 1722305501.7902, "task_type": "clustering", "type": "chat", "model": "embed-english-v3.0", "gen_params": {}, "start": 1722305501.567, "finish": 1722305501.7902, "ip": "", "conv_id": "94a661611dd14690a1f8ff341c608d33", "model_name": "embed-english-v3.0", "prompt": ["rock", "jazz", "classical", "flute", "guitar", "saxophone", "violin", "trumpet", "drums"], "ncluster": 2, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
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{"tstamp": 1722305515.7475, "task_type": "clustering", "type": "chat", "model": "intfloat/multilingual-e5-large-instruct", "gen_params": {}, "start": 1722305515.5586, "finish": 1722305515.7475, "ip": "", "conv_id": "90f3e443c24747bf937dc778bac550b7", "model_name": "intfloat/multilingual-e5-large-instruct", "prompt": ["rock", "jazz", "classical", "flute", "guitar", "saxophone", "violin", "trumpet", "drums", "Cassiopeia", "Scorpius", "Leo", "Impressionism", "Cubism", "Baroque"], "ncluster": 2, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
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{"tstamp": 1722305515.7475, "task_type": "clustering", "type": "chat", "model": "embed-english-v3.0", "gen_params": {}, "start": 1722305515.5586, "finish": 1722305515.7475, "ip": "", "conv_id": "94a661611dd14690a1f8ff341c608d33", "model_name": "embed-english-v3.0", "prompt": ["rock", "jazz", "classical", "flute", "guitar", "saxophone", "violin", "trumpet", "drums", "Cassiopeia", "Scorpius", "Leo", "Impressionism", "Cubism", "Baroque"], "ncluster": 2, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
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{"tstamp": 1722305517.51, "task_type": "clustering", "type": "chat", "model": "intfloat/multilingual-e5-large-instruct", "gen_params": {}, "start": 1722305517.3223, "finish": 1722305517.51, "ip": "", "conv_id": "90f3e443c24747bf937dc778bac550b7", "model_name": "intfloat/multilingual-e5-large-instruct", "prompt": ["rock", "jazz", "classical", "flute", "guitar", "saxophone", "violin", "trumpet", "drums", "Cassiopeia", "Scorpius", "Leo", "Impressionism", "Cubism", "Baroque"], "ncluster": 2, "output": "", "ndim": "2D (press for 3D)", "dim_method": "PCA", "clustering_method": "KMeans"}
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{"tstamp": 1722305517.51, "task_type": "clustering", "type": "chat", "model": "embed-english-v3.0", "gen_params": {}, "start": 1722305517.3223, "finish": 1722305517.51, "ip": "", "conv_id": "94a661611dd14690a1f8ff341c608d33", "model_name": "embed-english-v3.0", "prompt": ["rock", "jazz", "classical", "flute", "guitar", "saxophone", "violin", "trumpet", "drums", "Cassiopeia", "Scorpius", "Leo", "Impressionism", "Cubism", "Baroque"], "ncluster": 2, "output": "", "ndim": "2D (press for 3D)", "dim_method": "PCA", "clustering_method": "KMeans"}
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data/retrieval_battle-b9229914-47bc-4da8-a21b-89329fff8207.jsonl
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{"tstamp": 1722305246.8396, "task_type": "retrieval", "type": "rightvote", "models": ["", ""], "ip": "", "0_conv_id": "6cf9d4db20f8436c8c7f2ccaca29d2fa", "0_model_name": "sentence-transformers/all-MiniLM-L6-v2", "0_prompt": "what is the difference between cluster point and limit point?", "0_output": [["what is the difference between cluster point and limit point?", "Askubuntu Stackexchange\n\nQ: How to enable user sharing per instructions? I have this entry in .xsession-errors log\n\"Nautilus-Share-Message: Called \"net usershare info\" but it failed: 'net usershare' returned \nerror 255: net usershare: cannot open usershare directory /var/lib/samba/usershares. \nError No such file or directory\nPlease ask your system administrator to enable user sharing.\n\nThis is in relation to my applets having to be reloaded after every boot. Just wondering how I would enable user sharing, and how it affects my applets ??\n\nA: I don't think this effects your applets at all, that's probably a different bug. You could just make the directory with sudo:\nsudo mkdir -p /var/lib/samba/usershares\n\nBut I don't really know what it will do.\n"]], "0_corpus": "stackexchange", "1_conv_id": "38308d8cc72f4a24b8ddc6bafec79a96", "1_model_name": "BAAI/bge-large-en-v1.5", "1_prompt": "what is the difference between cluster point and limit point?", "1_output": [["what is the difference between cluster point and limit point?", "Math Stackexchange\n\nQ: Limit and limit points What is the basic difference between limit and limit points, and if a sequence has one unique limit how it can have a lot of limit points \n\nA: A limit point is a generalization of a limit (each limit is a limit point but not vice versa). You can see this in the definition:\nLimit: $a$ is a limit of $(a_n)$, iff in each neighborhood of $a$ are almost all elements of $(a_n)$.\nLimit point: $a$ is a limit of $(a_n)$, iff in each neighborhood of $a$ are infinite elements of $(a_n)$.\nI highlighted the difference between both definitions.\nBecause only infinite elements need to be in any neighborhood of $a$. There can be infinite elements outside this neighborhood which can clustered to another limit point. This is the reason why there might be many limit points for a sequence. If $a$ is a limit only finite elements can be outside any given neighborhood which is not enough to go to another limit.\n"]], "1_corpus": "stackexchange"}
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data/retrieval_individual-b9229914-47bc-4da8-a21b-89329fff8207.jsonl
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{"tstamp": 1722305178.7998, "task_type": "retrieval", "type": "chat", "model": "nomic-ai/nomic-embed-text-v1.5", "gen_params": {}, "start": 1722305178.5602, "finish": 1722305178.7998, "ip": "", "conv_id": "03037905b8a749e399e111e32c19baee", "model_name": "nomic-ai/nomic-embed-text-v1.5", "prompt": "what is the difference between an electronic signal and an electromagnetic signal?", "output": [["what is the difference between an electronic signal and an electromagnetic signal?", "Askubuntu Stackexchange\n\nQ: Trouble Installing libxp6 and multi-arch-support I am following this guide, but I have run into some difficulties at step 11. When I type\nsudo apt-get install ./libxp6_1.0.2-2_amd64.deb\n\nI get\nReading package lists... Done\nBuilding dependency tree \nReading state information... Done\nNote, selecting 'libxp6' instead of './libxp6_1.0.2-2_amd64.deb'\nSome packages could not be installed. This may mean that you have\nrequested an impossible situation or if you are using the unstable\ndistribution that some required packages have not yet been created\nor been moved out of Incoming.\nThe following information may help to resolve the situation:\n\nThe following packages have unmet dependencies:\n libxp6 : PreDepends: multiarch-support but it is not installable\nE: Unable to correct problems, you have held broken packages.\n\nlibxp6 and multiarch-support are what seem to be giving me difficulties. Searching on the web has given me a little, but not enough to install. Even the Ubuntu package website isn't helping.\nAny help would be appreciated.\n\nA: Then you have to install multiarch-support package from 18.04 LTS first with\ncd ~/Downloads\nwget http://archive.ubuntu.com/ubuntu/pool/main/g/glibc/multiarch-support_2.27-3ubuntu1_amd64.deb\nsudo apt-get install ./multiarch-support_2.27-3ubuntu1_amd64.deb\n\nand continue to follow the guide.\n"]], "corpus": "stackexchange"}
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{"tstamp": 1722305223.7026, "task_type": "retrieval", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1722305223.4442, "finish": 1722305223.7026, "ip": "", "conv_id": "9f4dfa402ea64c74bfec3768569b6d00", "model_name": "GritLM/GritLM-7B", "prompt": "How can deep learning be used to design communication systems as end-to-end reconstruction tasks? ", "output": [["How can deep learning be used to design communication systems as end-to-end reconstruction tasks? ", "Title: An Introduction to Deep Learning for the Physical Layer\n\nAbstract: We present and discuss several novel applications of deep learning for the physical layer. By interpreting a communications system as an autoencoder, we develop a fundamental new way to think about communications system design as an end-to-end reconstruction task that seeks to jointly optimize transmitter and receiver components in a single process. We show how this idea can be extended to networks of multiple transmitters and receivers and present the concept of radio transformer networks as a means to incorporate expert domain knowledge in the machine learning model. Lastly, we demonstrate the application of convolutional neural networks on raw IQ samples for modulation classification which achieves competitive accuracy with respect to traditional schemes relying on expert features. The paper is concluded with a discussion of open challenges and areas for future investigation."]], "corpus": "arxiv"}
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{"tstamp": 1722305223.7026, "task_type": "retrieval", "type": "chat", "model": "intfloat/e5-mistral-7b-instruct", "gen_params": {}, "start": 1722305223.4442, "finish": 1722305223.7026, "ip": "", "conv_id": "fb3390a4534f41758663e225ee7ed9a6", "model_name": "intfloat/e5-mistral-7b-instruct", "prompt": "How can deep learning be used to design communication systems as end-to-end reconstruction tasks? ", "output": [["How can deep learning be used to design communication systems as end-to-end reconstruction tasks? ", "Title: Design of Communication Systems using Deep Learning: A Variational Inference Perspective\n\nAbstract: Recent research in the design of end to end communication system using deep learning has produced models which can outperform traditional communication schemes. Most of these architectures leveraged autoencoders to design the encoder at the transmitter and decoder at the receiver and train them jointly by modeling transmit symbols as latent codes from the encoder. However, in communication systems, the receiver has to work with noise corrupted versions of transmit symbols. Traditional autoencoders are not designed to work with latent codes corrupted with noise. In this work, we provide a framework to design end to end communication systems which accounts for the existence of noise corrupted transmit symbols. The proposed method uses deep neural architecture. An objective function for optimizing these models is derived based on the concepts of variational inference. Further, domain knowledge such as channel type can be systematically integrated into the objective. Through numerical simulation, the proposed method is shown to consistently produce models with better packing density and achieving it faster in multiple popular channel models as compared to the previous works leveraging deep learning models."]], "corpus": "arxiv"}
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{"tstamp": 1722305178.7998, "task_type": "retrieval", "type": "chat", "model": "nomic-ai/nomic-embed-text-v1.5", "gen_params": {}, "start": 1722305178.5602, "finish": 1722305178.7998, "ip": "", "conv_id": "03037905b8a749e399e111e32c19baee", "model_name": "nomic-ai/nomic-embed-text-v1.5", "prompt": "what is the difference between an electronic signal and an electromagnetic signal?", "output": [["what is the difference between an electronic signal and an electromagnetic signal?", "Askubuntu Stackexchange\n\nQ: Trouble Installing libxp6 and multi-arch-support I am following this guide, but I have run into some difficulties at step 11. When I type\nsudo apt-get install ./libxp6_1.0.2-2_amd64.deb\n\nI get\nReading package lists... Done\nBuilding dependency tree \nReading state information... Done\nNote, selecting 'libxp6' instead of './libxp6_1.0.2-2_amd64.deb'\nSome packages could not be installed. This may mean that you have\nrequested an impossible situation or if you are using the unstable\ndistribution that some required packages have not yet been created\nor been moved out of Incoming.\nThe following information may help to resolve the situation:\n\nThe following packages have unmet dependencies:\n libxp6 : PreDepends: multiarch-support but it is not installable\nE: Unable to correct problems, you have held broken packages.\n\nlibxp6 and multiarch-support are what seem to be giving me difficulties. Searching on the web has given me a little, but not enough to install. Even the Ubuntu package website isn't helping.\nAny help would be appreciated.\n\nA: Then you have to install multiarch-support package from 18.04 LTS first with\ncd ~/Downloads\nwget http://archive.ubuntu.com/ubuntu/pool/main/g/glibc/multiarch-support_2.27-3ubuntu1_amd64.deb\nsudo apt-get install ./multiarch-support_2.27-3ubuntu1_amd64.deb\n\nand continue to follow the guide.\n"]], "corpus": "stackexchange"}
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{"tstamp": 1722305223.7026, "task_type": "retrieval", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1722305223.4442, "finish": 1722305223.7026, "ip": "", "conv_id": "9f4dfa402ea64c74bfec3768569b6d00", "model_name": "GritLM/GritLM-7B", "prompt": "How can deep learning be used to design communication systems as end-to-end reconstruction tasks? ", "output": [["How can deep learning be used to design communication systems as end-to-end reconstruction tasks? ", "Title: An Introduction to Deep Learning for the Physical Layer\n\nAbstract: We present and discuss several novel applications of deep learning for the physical layer. By interpreting a communications system as an autoencoder, we develop a fundamental new way to think about communications system design as an end-to-end reconstruction task that seeks to jointly optimize transmitter and receiver components in a single process. We show how this idea can be extended to networks of multiple transmitters and receivers and present the concept of radio transformer networks as a means to incorporate expert domain knowledge in the machine learning model. Lastly, we demonstrate the application of convolutional neural networks on raw IQ samples for modulation classification which achieves competitive accuracy with respect to traditional schemes relying on expert features. The paper is concluded with a discussion of open challenges and areas for future investigation."]], "corpus": "arxiv"}
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{"tstamp": 1722305223.7026, "task_type": "retrieval", "type": "chat", "model": "intfloat/e5-mistral-7b-instruct", "gen_params": {}, "start": 1722305223.4442, "finish": 1722305223.7026, "ip": "", "conv_id": "fb3390a4534f41758663e225ee7ed9a6", "model_name": "intfloat/e5-mistral-7b-instruct", "prompt": "How can deep learning be used to design communication systems as end-to-end reconstruction tasks? ", "output": [["How can deep learning be used to design communication systems as end-to-end reconstruction tasks? ", "Title: Design of Communication Systems using Deep Learning: A Variational Inference Perspective\n\nAbstract: Recent research in the design of end to end communication system using deep learning has produced models which can outperform traditional communication schemes. Most of these architectures leveraged autoencoders to design the encoder at the transmitter and decoder at the receiver and train them jointly by modeling transmit symbols as latent codes from the encoder. However, in communication systems, the receiver has to work with noise corrupted versions of transmit symbols. Traditional autoencoders are not designed to work with latent codes corrupted with noise. In this work, we provide a framework to design end to end communication systems which accounts for the existence of noise corrupted transmit symbols. The proposed method uses deep neural architecture. An objective function for optimizing these models is derived based on the concepts of variational inference. Further, domain knowledge such as channel type can be systematically integrated into the objective. Through numerical simulation, the proposed method is shown to consistently produce models with better packing density and achieving it faster in multiple popular channel models as compared to the previous works leveraging deep learning models."]], "corpus": "arxiv"}
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{"tstamp": 1722305229.7963, "task_type": "retrieval", "type": "chat", "model": "sentence-transformers/all-MiniLM-L6-v2", "gen_params": {}, "start": 1722305229.6152, "finish": 1722305229.7963, "ip": "", "conv_id": "6cf9d4db20f8436c8c7f2ccaca29d2fa", "model_name": "sentence-transformers/all-MiniLM-L6-v2", "prompt": "what is the difference between cluster point and limit point?", "output": [["what is the difference between cluster point and limit point?", "Askubuntu Stackexchange\n\nQ: How to enable user sharing per instructions? I have this entry in .xsession-errors log\n\"Nautilus-Share-Message: Called \"net usershare info\" but it failed: 'net usershare' returned \nerror 255: net usershare: cannot open usershare directory /var/lib/samba/usershares. \nError No such file or directory\nPlease ask your system administrator to enable user sharing.\n\nThis is in relation to my applets having to be reloaded after every boot. Just wondering how I would enable user sharing, and how it affects my applets ??\n\nA: I don't think this effects your applets at all, that's probably a different bug. You could just make the directory with sudo:\nsudo mkdir -p /var/lib/samba/usershares\n\nBut I don't really know what it will do.\n"]], "corpus": "stackexchange"}
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{"tstamp": 1722305229.7963, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722305229.6152, "finish": 1722305229.7963, "ip": "", "conv_id": "38308d8cc72f4a24b8ddc6bafec79a96", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "what is the difference between cluster point and limit point?", "output": [["what is the difference between cluster point and limit point?", "Math Stackexchange\n\nQ: Limit and limit points What is the basic difference between limit and limit points, and if a sequence has one unique limit how it can have a lot of limit points \n\nA: A limit point is a generalization of a limit (each limit is a limit point but not vice versa). You can see this in the definition:\nLimit: $a$ is a limit of $(a_n)$, iff in each neighborhood of $a$ are almost all elements of $(a_n)$.\nLimit point: $a$ is a limit of $(a_n)$, iff in each neighborhood of $a$ are infinite elements of $(a_n)$.\nI highlighted the difference between both definitions.\nBecause only infinite elements need to be in any neighborhood of $a$. There can be infinite elements outside this neighborhood which can clustered to another limit point. This is the reason why there might be many limit points for a sequence. If $a$ is a limit only finite elements can be outside any given neighborhood which is not enough to go to another limit.\n"]], "corpus": "stackexchange"}
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{"tstamp": 1722305252.6945, "task_type": "retrieval", "type": "chat", "model": "BM25", "gen_params": {}, "start": 1722305252.201, "finish": 1722305252.6945, "ip": "", "conv_id": "d56443b4b3064e69a3fc99eabc8fbf8f", "model_name": "BM25", "prompt": "mass effect 1 how many skill points total?", "output": [["mass effect 1 how many skill points total?", "Gaming Stackexchange\n\nQ: How many skill points will I have at max level? What is the maximum level in Mass Effect 3?\nHow many skill points will Shepard have at max level? \nIf NPC companions earn a different number of skill points than Shepard, what's the number they'll have at max level?\n\nA: Since this question seems to have been deemed the Canonical by mods:\nThe maximum character level is 60. At this level, Shepard will have earned a total of 181 Skill Points.\nMaxing a single skill requires 21 points.\nThere are enough points in the game to max out a total of 8 skills, with a few left over.\nShepard, conveniently enough, has 8 skills, plus one slot for a Bonus Power.\nSo, you can come very close to maxing out all skills, but you can't quite make it to maxing out all 9. You can max out 8 of them, and have 13 points remaining for the 9th, which lets you get to rank 4. You'll have 2 points left over. Alternately, you could max out 7 skills, get two to rank 5, and have 3 points left over.\n"]], "corpus": "stackexchange"}
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{"tstamp": 1722305252.6945, "task_type": "retrieval", "type": "chat", "model": "mixedbread-ai/mxbai-embed-large-v1", "gen_params": {}, "start": 1722305252.201, "finish": 1722305252.6945, "ip": "", "conv_id": "2766c8817d564f3fa47a1aa8eeaa0b03", "model_name": "mixedbread-ai/mxbai-embed-large-v1", "prompt": "mass effect 1 how many skill points total?", "output": [["mass effect 1 how many skill points total?", "Gaming Stackexchange\n\nQ: How many skill points will I have at max level? What is the maximum level in Mass Effect 3?\nHow many skill points will Shepard have at max level? \nIf NPC companions earn a different number of skill points than Shepard, what's the number they'll have at max level?\n\nA: Since this question seems to have been deemed the Canonical by mods:\nThe maximum character level is 60. At this level, Shepard will have earned a total of 181 Skill Points.\nMaxing a single skill requires 21 points.\nThere are enough points in the game to max out a total of 8 skills, with a few left over.\nShepard, conveniently enough, has 8 skills, plus one slot for a Bonus Power.\nSo, you can come very close to maxing out all skills, but you can't quite make it to maxing out all 9. You can max out 8 of them, and have 13 points remaining for the 9th, which lets you get to rank 4. You'll have 2 points left over. Alternately, you could max out 7 skills, get two to rank 5, and have 3 points left over.\n"]], "corpus": "stackexchange"}
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