{ "text": "大家好,這裡是人數解說。就在昨天,千萬3.8 Flash NEXT正式開源發佈1250億優勢的AI大模型。現在居然可以在本地電腦上進行部署運行。它是一個多模特的MOE緩活架構模型。每個Token實際只激活60億優勢。是千萬最新的下一代架構,也就是千萬4。它原生支持26.2萬上小文。擴張以後,甚至可以達到百萬Token。更誇張的是,低顯存用戶,可以用到的\n用硬盤來湊。甚至有人用3090,MacBook Pro來進行運行。而它真正厲害的地方,還不只是人跑。無論是代碼推電能力,還是Agent,性能都非常強悍。比如把它跟Cloud的Opus 5,還有GPT506速放在一起盲測,都達到了意想不到的效果。那麼問題來了,一個1250億優勢的開源模型,到底能跑出什麼效果?今天我們就直接通過一系列真實的案例,答應看看這千萬3.8最新的Flash NEXT模型,到底有多地谱。目前它的\n繼續EAV格式的模型以及同步發布。多個量化版以及同步發布的HanE Face開源社區。因為千萬3.8Flash NEXT模型,它支持CPU統一內存配置,以實現接近虛擬內存的速度。也就意味著,內存不夠,我們可以用硬盤來湊。接下來我們進行本地安裝部署實測下。在開始之前,首先我們去下載最新開源的千萬3.8Flash NEXT模型。\n我們先把這個千萬3.8Flash NEXT模型給它動下來。我們先把這個千萬3.8Flash NEXT模型給它動下來。我們先把它打開它,來進行下載一下。好,打開以後,它裡面有多個量化模型。到時候你可以根據這顯示出硬盤大小,來進行選擇。比如說選擇Q字版本。這裡面有三個模型文件,來進行動下來。我們把它放在桌面上。我們點下載。好,下載它以後,那麼第二個,全部都給它放在桌面上。最近好多人問這個下載器啊,這是一款TDM-FARDS的多線程下載器。\n下載大文件,大模型,速度超快。好,下載好第二個模型分訣以後。我們先返回去,來下載第三個模型分訣。同樣給它放在桌面上。我們點下載。我們稍等一會。它現在速度可以捧到將近每秒,將近100兆左右了。幾乎已經捧到Hugging Face的下載速度了。好,下載好模型文件以後。我們現在重新返回到剛才提示下。來執行第二步。接下來獲取下最新版本的NAMSAPP這款開業項目。那麼你先往打開它,先下載一下。我們需要用它來加載模型。打開以後,我們點下放最新版本。目前最新版本是V01.4.8.\n我們先在網上。我們打開它,先下載一下。打開以後,然後再往下載。來獲取的對型版本。第一個是MacOS版本。另外一個是Android以及Windows版本。到時候根據情況去選擇就可以了。比如說這裡選擇Windows版本。因為我是N考的,所以這位選擇COOTAD版本。當然如果你是A考的話,那選擇WGWG版本。這位選擇COOTAD13版本。這裡需要注意一下是這兩個文件都要下載。前面這個組程序,後面是想法去通文件。這兩個都要下載。我們下載。我們下載下來。比如說同樣給它放到桌面上。我們點下載。好,下載好第一個文件以後。\n我們先把它刀下來。然後把它放到桌面上。先下載一下。好,下載好以後,把它關閉掉。然後先把它夾出來。第二個,央桌包。全部夾出來。好,夾好以後,央桌包給它上掉。先把這NAMASPP組成序,我把它重命名一下。我們先把它重命名這NAMASPP。好,重命名好以後,先把這個區域文件給它放進去。放到這個NAMASPP根目錄下,拖上去就可以了。好,放入好以後,先打開它。先我們需要在根目錄下,來創建一個新建文件夾。我們需要給新建一個Modus50GWGWGWGWGWGWGWGWGWGWGWGWGWGW\n新建好以後,先打開它。先把我們剛下載好的這個模型文件給它放進來。這三個模型文件都給它放進去就可以了。好,放入好以後,現在重新返回到乾車帖下,來執行第三步。就來獲取一下這個一介啟的腳本。突然給它動下來。好,下載好以後,這裡面的參數你就可以自由調整。尤其上面這個模型這裡。如果下載的模型跟我不一樣的話,那麼一定要把這個模型名稱改成自己的。因為我當前的模型名稱是這個。也就是千萬3.8Flash,Nex,UD,IQ4,HS,Z,\n這個分卷。然後後面跟它分卷1到3。它就會自動價值三個分卷模型。然後其他優秀的話,你可以自由調整。那先來試一下。然後先把這個起動腳本給它放進去。放到NAMASPP根目錄下。好,放到後面我們先打開它。打開以後,先打開它。點擊打開。它現在開始加上模型了。我們稍等一會。好,當你看到這個鏈接的話,那說明它已經起動中空了。先打開試想,打開這個地址。打開燃燃器。打開這個地址。來試試想。可以啊,沒問題啊。\n它現在成功了。目前加在的模型的話,是千萬3.8Flash,Nex,UD,Q4電化板。沒問題啊。那先來試一下,看行不行啊。比方說明好,請自我介紹一下。\n好,說明好,有什麼第一發送一下。看一下能不能跑得動啊。我待機顯著是24GB的。內存的話是64GB。但硬盤比較大,是2T的。絕對是沒問題的。因為目前它是跑在我們硬盤上的。要得看一下它速度。目前可以跑在每秒是個頭肯左右。那先來跑一個任務。比如現在我讓它幫我編寫一個跑步遊戲。我們來試一下效果。\n我們來試一下。好,這樣的話它就開始了。我們找到一會。當前速度的話,同樣是每秒加近11個頭肯左右。這個過程可以需要幾分鐘到幾十分鐘。那先來看一下我當前硬件佔用。我當前內存是64GB的。幾乎已經跑滿了。佔用力90%左右。然後CPU的話,佔用力大概是70%左右。那先來看一下顯著。幾乎已經佔滿了。24GB的顯著幾乎已經跑了95%左右了。因為當前是通過MMAP,讓模型群眾跑在這個硬盤上的。所以我們看顯著。幾乎已經佔滿了。24GB的顯著幾乎已經跑了95%左右了。因為當前是通過MMAP,讓模型群眾跑在這個硬盤上的。所以\n所以雖然模型群眾超過的顯著。當它能量可以跑。當它完成以後,我們試一下效果。看看能否正常運行。我們點一下開始奔跑。哎呦,這樣的。哎,沒吃到。這個積分系統沒問題。哎,我怎麼都吃不到的。哎,越來越快了。哎呦,哦,創死了。我靠。\n再來一次。再來一次。\n再來一次。\n再來一次。\n再來一次。\n再來一次。\n再來一次。\n再來一次。\n嗯?\n嗯?\n它越來越快了。我靠。\n我靠。\n我靠。\n我靠。\n你們越來越快了。\n我靠。\n你們越來越快了。\n哎?\n哎?\n吼。\n吼。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。\n我靠。", "language": "zh", "duration": 553.813313, "segments": [ { "id": 0, "seek": 0, "start": 0.0, "end": 29.96, "text": "大家好,這裡是人數解說。就在昨天,千萬3.8 Flash NEXT正式開源發佈1250億優勢的AI大模型。現在居然可以在本地電腦上進行部署運行。它是一個多模特的MOE緩活架構模型。每個Token實際只激活60億優勢。是千萬最新的下一代架構,也就是千萬4。它原生支持26.2萬上小文。擴張以後,甚至可以達到百萬Token。更誇張的是,低顯存用戶,可以用到的", "tokens": [ 50365, 15248, 11, 18771, 1541, 4035, 30622, 17278, 4622, 1543, 3111, 3581, 47404, 6135, 11, 20787, 14099, 18, 13, 23, 20232, 12384, 20542, 15789, 27584, 8949, 47402, 14637, 1593, 230, 4762, 2803, 25459, 12827, 103, 7978, 95, 1546, 48698, 3582, 41908, 39823, 1543, 12648, 9636, 227, 5823, 6723, 3581, 8802, 10928, 20545, 21184, 99, 5708, 18214, 8082, 13470, 16469, 110, 32772, 8082, 1543, 11284, 1541, 8990, 6392, 41908, 17682, 1546, 18976, 36, 12608, 102, 25956, 7360, 114, 43362, 41908, 39823, 1543, 23664, 3338, 51, 8406, 10376, 34837, 14003, 26373, 222, 25956, 4550, 25459, 12827, 103, 7978, 95, 1543, 1541, 20787, 14099, 8661, 12560, 1546, 45271, 19105, 7360, 114, 43362, 11, 6404, 5620, 20787, 14099, 19, 1543, 11284, 19683, 8244, 35488, 10880, 13, 17, 14099, 5708, 7322, 17174, 1543, 13167, 112, 18889, 3588, 5661, 11, 17556, 20844, 6723, 33086, 4511, 31906, 14099, 51, 8406, 1543, 19002, 3549, 229, 18889, 24620, 11, 41377, 46605, 39781, 9254, 1486, 114, 11, 6723, 9254, 4511, 1546, 51863 ], "temperature": 0, "avg_logprob": -0.30598192273473446, "compression_ratio": 1.2331460674157304, "no_speech_prob": 1.1532942136016633e-11, "source": "whisper" }, { "id": 1, "seek": 3000, "start": 30.0, "end": 60.0, "text": "用硬盤來湊。甚至有人用3090,MacBook Pro來進行運行。而它真正厲害的地方,還不只是人跑。無論是代碼推電能力,還是Agent,性能都非常強悍。比如把它跟Cloud的Opus 5,還有GPT506速放在一起盲測,都達到了意想不到的效果。那麼問題來了,一個1250億優勢的開源模型,到底能跑出什麼效果?今天我們就直接通過一系列真實的案例,答應看看這千萬3.8最新的Flash NEXT模型,到底有多地谱。目前它的", "tokens": [ 50365, 9254, 38114, 105, 5419, 97, 3763, 33744, 232, 1543, 17556, 20844, 45820, 9254, 3446, 7771, 11, 34355, 19203, 1705, 3763, 18214, 8082, 32772, 8082, 1543, 11070, 11284, 6303, 15789, 20939, 1546, 30146, 11, 7824, 1960, 36859, 4035, 32585, 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"繼續EAV格式的模型以及同步發布。多個量化版以及同步發布的HanE Face開源社區。因為千萬3.8Flash NEXT模型,它支持CPU統一內存配置,以實現接近虛擬內存的速度。也就意味著,內存不夠,我們可以用硬盤來湊。接下來我們進行本地安裝部署實測下。在開始之前,首先我們去下載最新開源的千萬3.8Flash NEXT模型。", "tokens": [ 50365, 38459, 36, 32, 53, 30921, 27584, 1546, 41908, 39823, 40282, 13089, 31429, 14637, 34688, 1543, 6392, 3338, 26748, 23756, 42096, 40282, 13089, 31429, 14637, 34688, 1546, 39, 282, 36, 4047, 8949, 47402, 27658, 44526, 1543, 11471, 20787, 14099, 18, 13, 23, 25680, 1299, 12384, 20542, 41908, 39823, 11, 11284, 35488, 34, 8115, 33725, 2257, 28472, 39781, 38846, 34719, 11, 3588, 10376, 9581, 14468, 17463, 12026, 249, 13167, 105, 28472, 39781, 1546, 31217, 13127, 1543, 6404, 3111, 9042, 17268, 19382, 11, 28472, 39781, 1960, 31649, 11, 5884, 6723, 9254, 38114, 105, 5419, 97, 3763, 33744, 232, 1543, 40012, 5884, 18214, 8082, 8802, 10928, 16206, 44453, 13470, 16469, 110, 10376, 9592, 105, 4438, 1543, 3581, 21017, 32442, 11, 36490, 5884, 6734, 4438, 12290, 231, 8661, 12560, 8949, 47402, 1546, 20787, 14099, 18, 13, 23, 25680, 1299, 12384, 20542, 41908, 39823, 1543 ], "temperature": 0, "avg_logprob": -0.20114766114146998, "compression_ratio": 1.2643312101910829, "no_speech_prob": 2.40232972403831e-11, "source": "whisper" }, { "id": 3, "seek": 9000, "start": 90.0, "end": 120.0, "text": "我們先把這個千萬3.8Flash NEXT模型給它動下來。我們先把這個千萬3.8Flash NEXT模型給它動下來。我們先把它打開它,來進行下載一下。好,打開以後,它裡面有多個量化模型。到時候你可以根據這顯示出硬盤大小,來進行選擇。比如說選擇Q字版本。這裡面有三個模型文件,來進行動下來。我們把它放在桌面上。我們點下載。好,下載它以後,那麼第二個,全部都給它放在桌面上。最近好多人問這個下載器啊,這是一款TDM-FARDS的多線程下載器。", "tokens": [ 50365, 5884, 10108, 16075, 6287, 20787, 14099, 18, 13, 23, 25680, 1299, 12384, 20542, 41908, 39823, 17798, 11284, 12572, 27769, 1543, 5884, 10108, 16075, 6287, 20787, 14099, 18, 13, 23, 25680, 1299, 12384, 20542, 41908, 39823, 17798, 11284, 12572, 27769, 1543, 5884, 10108, 42061, 12467, 8949, 11284, 11, 3763, 18214, 8082, 4438, 12290, 231, 8861, 1543, 2131, 11, 12467, 8949, 3588, 5661, 11, 11284, 32399, 2412, 6392, 3338, 26748, 23756, 41908, 39823, 1543, 4511, 14010, 42766, 31337, 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"下載大文件,大模型,速度超快。好,下載好第二個模型分訣以後。我們先返回去,來下載第三個模型分訣。同樣給它放在桌面上。我們點下載。我們稍等一會。它現在速度可以捧到將近每秒,將近100兆左右了。幾乎已經捧到Hugging Face的下載速度了。好,下載好模型文件以後。我們現在重新返回到剛才提示下。來執行第二步。接下來獲取下最新版本的NAMSAPP這款開業項目。那麼你先往打開它,先下載一下。我們需要用它來加載模型。打開以後,我們點下放最新版本。目前最新版本是V01.4.8.", "tokens": [ 50365, 4438, 12290, 231, 3582, 17174, 20485, 11, 3582, 41908, 39823, 11, 31217, 13127, 19869, 10251, 1543, 2131, 11, 4438, 12290, 231, 2131, 49085, 41908, 39823, 6627, 5396, 96, 3588, 5661, 1543, 5884, 10108, 3316, 242, 49925, 11, 3763, 4438, 12290, 231, 35878, 3338, 41908, 39823, 6627, 5396, 96, 1543, 13089, 6180, 17798, 11284, 12744, 3581, 162, 5475, 8833, 5708, 1543, 5884, 8216, 4438, 12290, 231, 1543, 5884, 10415, 235, 10187, 2257, 6236, 1543, 11284, 12648, 31217, 13127, 6723, 26075, 100, 4511, 34168, 17463, 23664, 20956, 11, 34168, 17463, 6879, 2347, 228, 29457, 2289, 1543, 23575, 2930, 236, 25338, 26075, 100, 4511, 39, 697, 3249, 4047, 1546, 4438, 12290, 231, 31217, 13127, 2289, 1543, 2131, 11, 4438, 12290, 231, 2131, 41908, 39823, 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"我們先在網上。我們打開它,先下載一下。打開以後,然後再往下載。來獲取的對型版本。第一個是MacOS版本。另外一個是Android以及Windows版本。到時候根據情況去選擇就可以了。比如說這裡選擇Windows版本。因為我是N考的,所以這位選擇COOTAD版本。當然如果你是A考的話,那選擇WGWG版本。這位選擇COOTAD13版本。這裡需要注意一下是這兩個文件都要下載。前面這個組程序,後面是想法去通文件。這兩個都要下載。我們下載。我們下載下來。比如說同樣給它放到桌面上。我們點下載。好,下載好第一個文件以後。", "tokens": [ 50365, 5884, 10108, 3581, 26352, 5708, 1543, 5884, 12467, 8949, 11284, 11, 10108, 4438, 12290, 231, 8861, 1543, 12467, 8949, 3588, 5661, 11, 10213, 8623, 29510, 4438, 12290, 231, 1543, 3763, 29057, 110, 29436, 1546, 2855, 39823, 42096, 8802, 1543, 40760, 1541, 34355, 4367, 42096, 8802, 1543, 26202, 8990, 1541, 5289, 6490, 40282, 45813, 1509, 42096, 8802, 1543, 4511, 14010, 31337, 36841, 39391, 6734, 21625, 13167, 229, 36781, 2289, 1543, 36757, 4622, 18771, 21625, 13167, 229, 45813, 1509, 42096, 8802, 1543, 11471, 15914, 45, 26504, 1546, 11, 7239, 2664, 11160, 21625, 13167, 229, 34, 3783, 51, 6112, 42096, 8802, 1543, 21707, 13119, 32526, 32, 26504, 21358, 11, 4184, 21625, 13167, 229, 54, 38, 54, 38, 42096, 8802, 1543, 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"我們先把它刀下來。然後把它放到桌面上。先下載一下。好,下載好以後,把它關閉掉。然後先把它夾出來。第二個,央桌包。全部夾出來。好,夾好以後,央桌包給它上掉。先把這NAMASPP組成序,我把它重命名一下。我們先把它重命名這NAMASPP。好,重命名好以後,先把這個區域文件給它放進去。放到這個NAMASPP根目錄下,拖上去就可以了。好,放入好以後,先打開它。先我們需要在根目錄下,來創建一個新建文件夾。我們需要給新建一個Modus50GWGWGWGWGWGWGWGWGWGWGWGWGWGW", "tokens": [ 50365, 5884, 10108, 42061, 2437, 222, 27769, 1543, 10213, 42061, 12744, 4511, 162, 5475, 8833, 5708, 1543, 10108, 4438, 12290, 231, 8861, 1543, 2131, 11, 4438, 12290, 231, 2131, 3588, 5661, 11, 42061, 14899, 5196, 231, 29327, 1543, 10213, 10108, 42061, 1787, 122, 29741, 1543, 49085, 11, 1787, 106, 162, 5475, 23305, 1543, 38714, 1787, 122, 29741, 1543, 2131, 11, 1787, 122, 2131, 3588, 5661, 11, 1787, 106, 162, 5475, 23305, 17798, 11284, 5708, 29327, 1543, 10108, 16075, 2664, 45, 2865, 3160, 17755, 30052, 11336, 6346, 237, 11, 1654, 42061, 12624, 25236, 15940, 8861, 1543, 5884, 10108, 42061, 12624, 25236, 15940, 2664, 45, 2865, 3160, 17755, 1543, 2131, 11, 12624, 25236, 15940, 2131, 3588, 5661, 11, 10108, 16075, 6287, 44526, 16262, 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"新建好以後,先打開它。先把我們剛下載好的這個模型文件給它放進來。這三個模型文件都給它放進去就可以了。好,放入好以後,現在重新返回到乾車帖下,來執行第三步。就來獲取一下這個一介啟的腳本。突然給它動下來。好,下載好以後,這裡面的參數你就可以自由調整。尤其上面這個模型這裡。如果下載的模型跟我不一樣的話,那麼一定要把這個模型名稱改成自己的。因為我當前的模型名稱是這個。也就是千萬3.8Flash,Nex,UD,IQ4,HS,Z,", "tokens": [ 50365, 12560, 34157, 2131, 3588, 5661, 11, 10108, 12467, 8949, 11284, 1543, 10108, 16075, 5884, 16940, 4438, 12290, 231, 20715, 6287, 41908, 39823, 17174, 20485, 17798, 11284, 12744, 18214, 3763, 1543, 2664, 10960, 3338, 41908, 39823, 17174, 20485, 7182, 17798, 11284, 12744, 18214, 6734, 36781, 2289, 1543, 2131, 11, 12744, 14028, 2131, 3588, 5661, 11, 12648, 12624, 12560, 3316, 242, 8350, 4511, 39698, 25941, 4845, 244, 4438, 11, 3763, 16262, 115, 8082, 35878, 31429, 1543, 3111, 3763, 29057, 110, 29436, 8861, 6287, 2257, 30312, 3284, 253, 1546, 49595, 8802, 1543, 40859, 5823, 17798, 11284, 12572, 27769, 1543, 2131, 11, 4438, 12290, 231, 2131, 3588, 5661, 11, 18771, 8833, 1546, 47375, 30622, 2166, 36781, 45233, 32943, 27662, 1543, 1530, 97, 9572, 49750, 6287, 41908, 39823, 18771, 1543, 13119, 4438, 12290, 231, 1546, 41908, 39823, 9678, 25395, 22977, 21358, 11, 20504, 48161, 16075, 6287, 41908, 39823, 15940, 49606, 34490, 11336, 17645, 1546, 1543, 11471, 1654, 13118, 8945, 1546, 41908, 39823, 15940, 49606, 1541, 6287, 1543, 6404, 5620, 20787, 14099, 18, 13, 23, 25680, 1299, 11, 45, 3121, 11, 9438, 11, 40, 48, 19, 11, 39, 50, 11, 57, 11 ], "temperature": 0, "avg_logprob": -0.26101936178004487, "compression_ratio": 1.4515306122448979, "no_speech_prob": 1.631006441016325e-11, "source": "whisper" }, { "id": 8, "seek": 24000, "start": 240.0, "end": 270.0, "text": "這個分卷。然後後面跟它分卷1到3。它就會自動價值三個分卷模型。然後其他優秀的話,你可以自由調整。那先來試一下。然後先把這個起動腳本給它放進去。放到NAMASPP根目錄下。好,放到後面我們先打開它。打開以後,先打開它。點擊打開。它現在開始加上模型了。我們稍等一會。好,當你看到這個鏈接的話,那說明它已經起動中空了。先打開試想,打開這個地址。打開燃燃器。打開這個地址。來試試想。可以啊,沒問題啊。", "tokens": [ 50365, 6287, 6627, 5322, 115, 1543, 10213, 5661, 8833, 9678, 11284, 6627, 5322, 115, 16, 4511, 18, 1543, 11284, 47778, 9722, 12572, 45441, 40242, 10960, 3338, 6627, 5322, 115, 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-0.3558761347895083, "compression_ratio": 1.5795454545454546, "no_speech_prob": 3.083923047486614e-11, "source": "whisper" }, { "id": 9, "seek": 27000, "start": 270.0, "end": 282.0, "text": "它現在成功了。目前加在的模型的話,是千萬3.8Flash,Nex,UD,Q4電化板。沒問題啊。那先來試一下,看行不行啊。比方說明好,請自我介紹一下。", "tokens": [ 50365, 11284, 12648, 11336, 32311, 2289, 1543, 39004, 9990, 3581, 1546, 41908, 39823, 21358, 11, 1541, 20787, 14099, 18, 13, 23, 25680, 1299, 11, 45, 3121, 11, 9438, 11, 48, 19, 20545, 23756, 43664, 1543, 4913, 17197, 4905, 1543, 4184, 10108, 3763, 22099, 8861, 11, 4200, 8082, 24151, 4905, 1543, 11706, 9249, 4622, 11100, 2131, 11, 16302, 9722, 1654, 30312, 38193, 8861, 1543, 50965 ], "temperature": 0, "avg_logprob": -0.3644636863189218, "compression_ratio": 1.4577114427860696, "no_speech_prob": 1.923042627915983e-11, "source": "whisper" }, { "id": 10, "seek": 27000, "start": 282.0, "end": 300.0, "text": "好,說明好,有什麼第一發送一下。看一下能不能跑得動啊。我待機顯著是24GB的。內存的話是64GB。但硬盤比較大,是2T的。絕對是沒問題的。因為目前它是跑在我們硬盤上的。要得看一下它速度。目前可以跑在每秒是個頭肯左右。那先來跑一個任務。比如現在我讓它幫我編寫一個跑步遊戲。我們來試一下效果。", "tokens": [ 50965, 2131, 11, 4622, 11100, 2131, 11, 2412, 7598, 18049, 14637, 29309, 8861, 1543, 28324, 8225, 28590, 32585, 5916, 12572, 4905, 1543, 1654, 18390, 17543, 46605, 19382, 1541, 7911, 8769, 1546, 1543, 28472, 39781, 21358, 1541, 19395, 8769, 1543, 8395, 38114, 105, 5419, 97, 25174, 3582, 11, 1541, 17, 51, 1546, 1543, 6948, 243, 2855, 1541, 4913, 17197, 1546, 1543, 11471, 39004, 11284, 1541, 32585, 3581, 5884, 38114, 105, 5419, 97, 5708, 1546, 1543, 4275, 5916, 28324, 11284, 31217, 13127, 1543, 39004, 6723, 32585, 3581, 23664, 20956, 1541, 3338, 19921, 14356, 107, 29457, 1543, 4184, 10108, 3763, 32585, 8990, 26443, 39517, 1543, 36757, 12648, 1654, 21195, 11284, 32187, 1654, 12608, 101, 4510, 104, 8990, 32585, 31429, 43046, 1543, 5884, 3763, 22099, 8861, 43076, 9319, 1543, 51865 ], "temperature": 0, "avg_logprob": -0.3644636863189218, "compression_ratio": 1.4577114427860696, "no_speech_prob": 1.923042627915983e-11, "source": "whisper" }, { "id": 11, "seek": 30000, "start": 300.0, "end": 330.0, "text": "我們來試一下。好,這樣的話它就開始了。我們找到一會。當前速度的話,同樣是每秒加近11個頭肯左右。這個過程可以需要幾分鐘到幾十分鐘。那先來看一下我當前硬件佔用。我當前內存是64GB的。幾乎已經跑滿了。佔用力90%左右。然後CPU的話,佔用力大概是70%左右。那先來看一下顯著。幾乎已經佔滿了。24GB的顯著幾乎已經跑了95%左右了。因為當前是通過MMAP,讓模型群眾跑在這個硬盤上的。所以我們看顯著。幾乎已經佔滿了。24GB的顯著幾乎已經跑了95%左右了。因為當前是通過MMAP,讓模型群眾跑在這個硬盤上的。所以", "tokens": [ 50365, 5884, 3763, 22099, 8861, 1543, 2131, 11, 8377, 21358, 11284, 3111, 21017, 2289, 1543, 5884, 25085, 4511, 2257, 6236, 1543, 13118, 8945, 31217, 13127, 21358, 11, 13089, 6180, 1541, 23664, 20956, 9990, 17463, 5348, 3338, 19921, 14356, 107, 29457, 1543, 6287, 8816, 29649, 6723, 35748, 23575, 32611, 4511, 23575, 20145, 32611, 1543, 4184, 10108, 3763, 28324, 1654, 13118, 8945, 38114, 105, 20485, 1593, 242, 9254, 1543, 1654, 13118, 8945, 28472, 39781, 1541, 19395, 8769, 1546, 1543, 23575, 2930, 236, 25338, 32585, 32197, 2289, 1543, 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"id": 12, "seek": 33000, "start": 330.0, "end": 358.6, "text": "所以雖然模型群眾超過的顯著。當它能量可以跑。當它完成以後,我們試一下效果。看看能否正常運行。我們點一下開始奔跑。哎呦,這樣的。哎,沒吃到。這個積分系統沒問題。哎,我怎麼都吃不到的。哎,越來越快了。哎呦,哦,創死了。我靠。", "tokens": [ 50365, 7239, 6306, 244, 5823, 41908, 39823, 7248, 97, 29595, 19869, 8816, 1546, 46605, 19382, 1543, 13118, 11284, 8225, 26748, 6723, 32585, 1543, 13118, 11284, 41509, 3588, 5661, 11, 5884, 22099, 8861, 43076, 9319, 1543, 22884, 8225, 45334, 15789, 11279, 32772, 8082, 1543, 5884, 8216, 8861, 21017, 1881, 242, 32585, 1543, 26755, 3606, 99, 11, 39425, 1543, 26755, 11, 4913, 10123, 4511, 1543, 6287, 13740, 235, 6627, 25368, 33725, 4913, 17197, 1543, 26755, 11, 1654, 11614, 7182, 10123, 35728, 1546, 1543, 26755, 11, 25761, 3763, 25761, 10251, 2289, 1543, 26755, 3606, 99, 11, 14659, 11, 5935, 113, 16989, 2289, 1543, 1654, 5363, 254, 1543, 51795 ], "temperature": 0, "avg_logprob": -0.35781680413012235, "compression_ratio": 1.3620689655172413, "no_speech_prob": 2.3698121590087773e-11, "source": "whisper" }, 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