PAI提供多种已经训练好的多模态智能处理类模型供您使用,包括图文匹配和图文生成模型。

ModelHub登录入口

您可以通过如下方法进入ModelHub:
  1. 登录PAI控制台
  2. 在左侧导航栏,单击模型管理及优化
  3. PAI模型管理页面,单击ModelHub页签。

图片文本匹配模型

  • 模型介绍

    基于电商场景训练的图片文本多模态匹配模型。

  • 输入数据
    输入数据为JSON格式字符串,包含图片的url字段和对应的文本,格式如下。
    {
      "input": {
        "url": "输入图片的URL",
        "text": "xxxxx"
      }
    }
  • 输出数据
    输出数据为JSON格式字符串,包含的字段如下表所示。
    字段 描述 Shape Type
    feature 多模态特征 [] STRING
    score 图文匹配得分 [] STRING
  • 示例
    例如,为该模型输入如下测试数据。
    {"input" : {"url" : "http://yq*****.oss-cn-hangzhou-zmf.aliyuncs.com/1605011268310-04ad2184-a85f-4e05-9ad1-cc8d4374****.png",
               "text" : "高腰开叉阔腿裤女春秋学生韩版宽松大码胖mm显瘦休闲直筒200斤冬"}
    系统输出如下结果。
    {
       "score": "0.99182093", 
       "feature": "0.5913938,0.13762167,-0.91001725,0.8861273,0.70018744,0.8021288,-0.9388965,0.3197481,0.7579089,0.74281895,0.60905606,-0.9265264,-0.9574535,0.1034148,-0.64083636,0.13672167,-0.4596075,-0.47999042,0.24380802,-0.50254107,0.92715174,-0.7685263,-0.82895446,0.9378043,-0.17363304,-0.2227173,0.487518,0.2940975,-0.7094649,-0.41321266,0.72392017,-0.65110314,0.31217682,-0.790735,0.6027367,-0.49360877,-0.059012517,-0.27428693,-0.7123376,-0.38725305,0.031377412,-0.3623875,0.9004798,0.63070554,-0.3568453,0.05002684,-0.3240582,-0.45369405,-0.6195787,0.8222992,0.6651849,0.77210176,-0.8029835,0.92798877,-0.11871383,0.44817185,0.16303186,0.07269271,-0.18169068,0.9090096,0.8308523,-0.73519593,0.7829337,0.093662106,0.6597115,-0.46106517,-0.0071462034,0.8104179,0.89372885,0.21279836,0.8955463,0.9579847,0.23179597,0.8499617,0.0045722583,-0.9681053,0.56340027,-0.10537529,-0.7230949,0.7802324,0.29230908,-0.69920117,-0.46734908,0.6259903,0.5023259,-0.5063412,0.092248306,-0.102055036,-0.7811699,0.9250194,-0.08501192,-0.20185211,0.06575388,-0.326157,0.13729516,0.107246324,-0.52018124,0.5821601,-0.2680246,0.8597336,-0.21241908,-0.23622131,0.9033321,0.83723295,-0.7548138,-0.58275497,-0.24080533,0.7860936,0.54661554,0.21193965,-0.008399446,0.6200189,0.972728,-0.37298256,-0.05166018,0.69285023,-0.42906138,-0.8206754,-0.7241641,0.97810024,-0.16160807,-0.18757743,-0.9677158,0.5231899,0.3078903,-0.3297478,-0.34939355,-0.31460825,-0.94175863,0.23362252,0.53444517,0.19419575,0.6568017,0.14880727,0.8441557,-0.41984403,-0.48784336,0.37309265,0.6743334,-0.7050426,-0.529256,-0.6925089,0.7887344,0.22677404,0.3495552,-0.6592281,-0.4883368,-0.2201489,-0.91029423,0.9078555,-0.10518587,0.8276125,-0.6443263,0.89165235,-0.21802342,-0.26681256,0.71308565,0.9503447,0.106346555,-0.5823493,0.88468504,-0.98366576,-0.2732497,-0.10867633,-0.6686611,0.29649043,-0.14533114,-0.3554921,-0.628675,-0.8498302,0.22116542,-0.5465438,-0.43509778,0.41746235,-0.8226383,-0.24232695,0.1586732,-0.20949359,-0.968111,-0.028535716,0.76694626,0.047005806,-0.86224544,0.5004287,-0.58666956,0.85184926,0.77280235,-0.8942109,-0.59883225,0.3243829,0.48704895,-0.65643716,0.18420874,-0.640697,0.023637932,-0.19650473,-0.8801892,-0.411531,-0.1579994,0.5471377,0.8532256,0.6990904,0.73159295,0.98453796,-0.32644522,-0.37597293,-0.40725493,0.5258676,-0.1443378,0.12797664,-0.23737021,0.39768788,0.5296632,0.926311,-0.32722685,0.31213498,0.005213115,0.958904,-0.5530387,0.8556193,-0.24709158,-0.45157632,-0.5270512,0.5373637,-0.9860768,-0.89657843,0.98305637,0.30264345,0.6857612,0.7814923,0.9733637,-0.9933925,0.6892766,0.18056639,0.4634681,-0.93717486,-0.9753518,0.46848705,-0.40974823,0.9463229,0.22990474,0.6597829,0.376035,-0.8394651,-0.4007167,-0.29144502,0.038682982,0.38042152,-0.29489034,-0.26374206,-0.9142611,0.24903092,0.6405866,-0.7789727,-0.9931288,0.5220771,-0.083224334,-0.5072596,0.9417732,-0.19532733,-0.6571721,0.70274806,0.71898174,-0.56941605,0.7324651,-0.53510725,-0.49177858,-0.51180613,-0.45828894,-0.8990464,-0.16062133,-0.35216975,-0.7115305,0.4048339,0.16430257,0.77867687,0.38833055,0.058456294,0.770261,0.39103237,0.21437146,-0.9381535,-0.6634451,0.32735294,-0.8091193,0.24826859,0.18731041,-0.8446281,0.7045958,0.63558805,-0.13515261,-0.57153165,-0.59529257,-0.61440635,0.904741,0.09871695,0.98048794,-0.28379378,0.45403343,-0.40081435,0.7826729,0.86030763,-0.96903414,0.3343622,0.82247925,-0.82013726,0.7923528,-0.6651119,-0.57553554,0.5674135,0.36722997,0.024742648,0.88357294,0.86471623,0.70793676,0.012471767,0.23163615,-0.56724524,-0.9161362,-0.88120526,-0.17518286,-0.05838405,0.009854151,-0.22678089,-0.85018647,0.13681777,0.65849113,0.26066172,-0.26400724,0.58941567,-0.98661053,-0.28984442,0.08229023,-0.45197022,-0.13106243,-0.43779656,-0.9154969,-0.79586154,0.34487385,-0.23121376,-0.21233258,0.67701095,0.9508768,0.8504902,0.026849559,-0.49117285,-0.37794805,0.050189324,-0.16284703,0.32846993,-0.41313076,0.47374228,-0.9103261,0.27885565,0.18941244,-0.95709145,0.96419483,0.7973295,0.79099727,0.86176306,-0.035309516,0.35990524,0.899763,0.7537747,0.63281643,-0.2867209,0.50530994,-0.10034622,0.097322844,-0.21189715,0.8326915,-0.6871527,-0.07315452,0.9308416,-0.64060867,-0.34400246,-0.16177468,-0.76823175,0.1145865,0.017910788,0.8825032,0.35439917,0.32770824,-0.72368824,0.26394957,0.38042015,0.93867767,-0.90773153,-0.979288,-0.23477694,-0.19299182,-0.4977122,-0.7783066,-0.053610478,0.09629531,-0.767824,-0.9273379,-0.07012768,0.74834925,-0.24355093,0.74379313,0.79528344,-0.4544574,-0.42005563,-0.7758413,-0.16620015,-0.42596358,0.52295244,0.84933704,-0.020719498,-0.9550239,-0.43687496,-0.15129915,0.07486725,0.14571506,-0.927716,0.8480543,-0.9259551,-0.8936599,0.2384449,0.80495274,0.5126097,0.6419454,-0.4881221,-0.066848405,0.9206399,0.8784409,0.26923874,-0.11703751,-0.5100766,0.7969016,0.40630686,0.9121792,-0.45438263,0.78272724,0.15503435,0.41817665,0.18565615,-0.31286877,-0.39144623,-0.9473047,0.2590472,0.50284183,0.28295344,-0.3488085,0.63219607,-0.049085684,0.9818534,0.97769386,0.17128825,0.23602775,0.858401,-0.15478,0.2600651,-0.8519777,0.6539445,0.40207255,0.9718055,-0.4499605,-0.46642628,0.6992271,0.60466146,-0.28153273,-0.7765994,-0.92182827,-0.55363107,0.819551,0.9101322,-0.5237633,0.26723334,-0.315352,-0.21080877,0.51094675,0.8466683,0.6990884,0.30920318,-0.7418709,0.85473156,0.6296211,0.88926667,0.57844865,-0.5845928,0.7060699,0.3303856,0.797856,-0.31138986,-0.8113813,0.18233404,0.48961607,0.72518736,0.831417,-0.17004597,-0.42082512,0.613252,-0.3964432,-0.31596315,0.30993694,-0.33003888,-0.8457364,0.506978,0.7138176,-0.8915566,-0.74094343,0.27951255,-0.36777154,0.31150293,-0.74095845,0.30061674,-0.9790283,-0.4780961,0.23184901,-0.5036929,0.8297752,-0.004898647,-0.9624664,0.76510775,-0.63323534,-0.42762932,-0.43488163,-0.37915862,0.65328616,-0.1723768,0.5269028,0.42822564,0.570707,0.71657693,-0.21293499,-0.14823182,-0.59327304,0.06845732,-0.31405586,0.624409,-0.8282087,0.307368,0.4376558,-0.9685839,0.63391113,-0.008294456,0.66503906,0.93096185,0.5838147,-0.9425848,-0.35357776,-0.33197656,0.6956333,-0.70333374,-0.28446776,-0.6482837,0.6589843,0.99184763,-0.85288733,0.11494227,0.011667575,-0.1093785,-0.31527677,0.5073648,0.34397167,0.0069509074,-0.26113552,-0.98517334,-0.084465556,-0.06398111,0.081339754,-0.91002136,0.65369123,-0.15633482,-0.018594863,-0.24016799,-0.68210226,-0.39808264,-0.628995,0.33521423,0.40918973,0.13802664,-0.8219445,0.6010021,0.053363916,-0.9921509,0.9380325,-0.8983411,-0.3761203,0.5539853,0.8269925,0.021206582,0.85229784,0.3545768,0.30604228,-0.8279735,0.054435328,-0.19952552,-0.93973565,-0.52697927,-0.2268469,-0.31357503,0.13031687,0.7277525,0.271896,0.22887471,0.0974392,0.80109996,-0.7166507,-0.4734176,-0.7466938,0.54020095,0.287631,-0.29010084,-0.47211942,-0.91772693,0.28806993,0.008239455,-0.66029,-0.22450411,-0.8677552,0.12715656,-0.5631571,0.5630608,0.58655363,-0.60747755,-0.18587297,0.37965995,0.48940387,0.92838025,-0.45735115,0.82355,-0.64993346,-0.8835211,0.67292815,0.8015672,0.8976497,-0.6576771,0.30035558,-0.79173565,0.5230248,-0.6033511,0.81660426,0.5374798,0.48666963,0.47239664,-0.64610195,-0.7821416,0.93703294,-0.36644047,-0.8543366,-0.31843707,0.9413576,-0.7958896,0.0593426,0.70289135,0.9592988,0.8676889,-0.9554874,-0.30762708,-0.33488035,-0.36450213,0.15804854,-0.71993786,0.81590307,-0.6321681,0.97830063,0.20229378,0.6646085,0.4059343,-0.8736555,0.68929505,0.10847979,-0.18394586,0.39713636,-0.2919363,-0.0070403023,0.9330139,0.95361286,-0.6557182,0.053437002,-0.40316874,-0.8676064,-0.82014215,-0.28445968,-0.7251426,0.008746826,-0.95702094,-0.6384773,0.90246093,-0.7969162,0.6398345,-0.25039753,-0.93341535,-0.76718736,0.7403101,0.6550914,-0.14856076,-0.20635594,0.9599992,-0.9846392,0.7403332,0.65394056,0.07848905,-0.21172377,0.51220584,-0.91411126,0.31456843,0.5019208,0.596681,0.71835303,-0.2884852,-0.36401334,-0.54740286,-0.052521262,-0.32767957,0.9471524,0.33138868,0.71468675,-0.0121267345,0.73399794,-0.8637489,-0.9861016,0.21532969,0.5350189,-0.9193123,0.2752033,-0.76450527,0.75134826,0.22399455,0.9589056,0.61734843,0.95075715,-0.7720206,0.4310934,-0.12244314,0.9175774,-0.0015274498,-0.08199289,0.3621118,0.3326951,-0.60653126,-0.89942145,-0.10527157,-0.9970921,-0.32819062,-0.50768363,-0.5554178,-0.1356669,0.81321454,0.088321835,-0.25389996,0.7848683,0.6758324,-0.41063288,0.9784589,0.54482764,-0.9269737,-0.09554822,0.9236298,-0.84249616,0.641373,0.3847215,-0.9747996,-0.75423896,-0.09445807,-0.884194,-0.8154002,0.3242017,0.08542202,0.9570408,-0.17123064,-0.30812213,0.6060362,0.08176672,0.54627156"
    }

视频文本匹配模型

  • 模型介绍

    基于电商场景训练的视频文本多模态匹配模型。

  • 输入数据
    输入数据为JSON格式字符串,包含图片的url字段和对应的文本,格式如下。
    {
      "input": {
        "url": "输入视频的URL",
        "text": "xxxxx"
      }
    }
  • 输出数据
    输出数据为JSON格式字符串,包含的字段如下表所示。
    字段 描述 Shape Type
    feature 多模态特征 [] STRING
    score 图文匹配得分 [] STRING
  • 示例
    例如,为该模型输入如下测试数据。
    {"input" : {"url" : "http://pai-vision-data-sh.oss-cn-shanghai-internal.aliyuncs.com/tmp/5000563****.mp4",
               "text" : "高腰开叉阔腿裤女春秋学生韩版宽松大码胖mm显瘦休闲直筒200斤冬"}
    系统输出如下结果。
    {
        "score": "0.99182093",
        "feature": 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