getting_started.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/sindhumadhavan/GitHub/transformers/.venv/lib/python3.9/site-packages/urllib3/__init__.py:35: NotOpenSSLWarning: urllib3 v2 only supports OpenSSL 1.1.1+, currently the 'ssl' module is compiled with 'LibreSSL 2.8.3'. See: https://github.com/urllib3/urllib3/issues/3020\n",
      "  warnings.warn(\n",
      "/Users/sindhumadhavan/GitHub/transformers/.venv/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    }
   ],
   "source": [
    "import librosa\n",
    "import pytesseract\n",
    "import soundfile\n",
    "\n",
    "from transformers import pipeline\n",
    "from transformers.pipelines.pt_utils import KeyDataset\n",
    "from datasets import load_dataset\n",
    "from pytesseract import Output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No model was supplied, defaulted to facebook/wav2vec2-base-960h and revision 55bb623 (https://huggingface.co/facebook/wav2vec2-base-960h).\n",
      "Using a pipeline without specifying a model name and revision in production is not recommended.\n",
      "Some weights of the model checkpoint at facebook/wav2vec2-base-960h were not used when initializing Wav2Vec2ForCTC: ['wav2vec2.encoder.pos_conv_embed.conv.weight_g', 'wav2vec2.encoder.pos_conv_embed.conv.weight_v']\n",
      "- This IS expected if you are initializing Wav2Vec2ForCTC from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
      "- This IS NOT expected if you are initializing Wav2Vec2ForCTC from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
      "Some weights of Wav2Vec2ForCTC were not initialized from the model checkpoint at facebook/wav2vec2-base-960h and are newly initialized: ['wav2vec2.encoder.pos_conv_embed.conv.parametrizations.weight.original0', 'wav2vec2.encoder.pos_conv_embed.conv.parametrizations.weight.original1', 'wav2vec2.masked_spec_embed']\n",
      "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
     ]
    }
   ],
   "source": [
    "transcriber = pipeline(task=\"automatic-speech-recognition\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'text': 'I HAVE A DREAM BUT ONE DAY THIS NATION WILL RISE UP LIVE UP THE TRUE MEANING OF ITS TREES'}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transcriber(\"https://huggingface.co/datasets/Narsil/asr_dummy/resolve/main/mlk.flac\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
     ]
    }
   ],
   "source": [
    "transcriber = pipeline(model=\"openai/whisper-large-v2\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Due to a bug fix in https://github.com/huggingface/transformers/pull/28687 transcription using a multilingual Whisper will default to language detection followed by transcription instead of translation to English.This might be a breaking change for your use case. If you want to instead always translate your audio to English, make sure to pass `language='en'`.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'text': ' I have a dream that one day this nation will rise up and live out the true meaning of its creed.'}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transcriber(\"https://huggingface.co/datasets/Narsil/asr_dummy/resolve/main/mlk.flac\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "My example 0.0.50 (and even older) is a different matter. In its early development form the standard is the current-day WSD-3 specification, which was developed as one of the first open source standards to include hardware control\n",
      "My example 1 - for example, you can find the list of 'deleted' files on your local filesystem... 1 2 3 4 5 6 7 8 9 10 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28\n",
      "My example 2: If the player was really unlucky and it was in their favor, instead of a 2-1 situation against Fnatic, they should have chosen a 3-0 and maybe pushed mid laner Maokai's gank if needed.\n",
      "My example 3 is a lot more comfortable having a nice little \"T-shirt\" that doesn't include a collar.  I think the collar of a \"T-shirt\" looks pretty neat at this point. The only downside to my T-\n",
      "My example 4\" and 5\" are designed with your eye in mind, so these will be easy to order.\n",
      "My example 5 is an example which uses the same language of SQL as MySQL on its own, and does not use the following syntax with more sophisticated syntax: CREATE TABLE names, PRIMARY KEY ( varchar(100), 1 ), PR\n",
      "My example 6x is a large square filled with 4 small squares. The squares should contain (with my example): (4 / 2)\n",
      "\n",
      "#9 \"square\" or 4x\n",
      "\n",
      "The next step is to work on the \"square\n",
      "My example 7 of the 11 in this tutorial came together the day after I was hired. I also was able to get my start in engineering before I took my first job in San Francisco, but I had to change jobs several times in a month.\n",
      "My example 811 would be the standard 6-9 year olds, with a few more of a back of the envelope, or a high school age. My child would probably come up to 4 and 8 in a row, depending on their age and\n",
      "My example 9 has a really interesting one, what I refer to as the 'Mental Flavour'. It is a form of anxiety, in my experience. It is something that is, in my opinion, rather more complicated than the physical feeling of\n"
     ]
    }
   ],
   "source": [
    "### using pipelines on a dataset\n",
    "def data():\n",
    "    for i in range(10):\n",
    "        yield f\"My example {i}\"\n",
    "\n",
    "\n",
    "pipe = pipeline(model=\"openai-community/gpt2\", pad_token_id=50256)\n",
    "generated_characters = 0\n",
    "for out in pipe(data()):\n",
    "    print(out[0][\"generated_text\"])\n",
    "    generated_characters += len(out[0][\"generated_text\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Some weights of Wav2Vec2ForCTC were not initialized from the model checkpoint at hf-internal-testing/tiny-random-wav2vec2 and are newly initialized: ['wav2vec2.encoder.pos_conv_embed.conv.parametrizations.weight.original0', 'wav2vec2.encoder.pos_conv_embed.conv.parametrizations.weight.original1', 'wav2vec2.feature_extractor.conv_layers.1.layer_norm.bias', 'wav2vec2.feature_extractor.conv_layers.1.layer_norm.weight', 'wav2vec2.feature_extractor.conv_layers.2.layer_norm.bias', 'wav2vec2.feature_extractor.conv_layers.2.layer_norm.weight']\n",
      "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n",
      "/Users/sindhumadhavan/GitHub/transformers/.venv/lib/python3.9/site-packages/datasets/load.py:1461: FutureWarning: The repository for hf-internal-testing/librispeech_asr_dummy contains custom code which must be executed to correctly load the dataset. You can inspect the repository content at https://hf.co/datasets/hf-internal-testing/librispeech_asr_dummy\n",
      "You can avoid this message in future by passing the argument `trust_remote_code=True`.\n",
      "Passing `trust_remote_code=True` will be mandatory to load this dataset from the next major release of `datasets`.\n",
      "  warnings.warn(\n"
     ]
    },
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<s>O ZM B X DCZ ZOQFCX B G ZCOBZ S</s> BYBO ZMY N WZ BO CBXS ZEBF FZ GB YC OY OMC GT B O CBW  EB BX B  XF        OBCF FWBZWB O MB  OOBZ W Z YBO S B CMZ WBEBBZ OBWFXZ CB OFGW FG S O W CZ W BZ Q CZ  CZWWBUE OWFW  ZBZESE BB EZH OZ C FQ BXC DC Y C Z SWB YZ XZ WZBW B MBW BZEWBU B Z BB BE B BX CB B ZB  BESE\"}\n",
      "{'text': \"O HW ZRBMCUBC WOG O YXZNYQOHWZV GF WZ GEKWBF  UOQ QS ZCBT B E C YOUECBEB FB CBBCBB EO ECBE BUZTHBB CFCBEO CZ Z Q W FSS  C F O B BWWCBEHWB BWCWXMCBMNB WCBVMOZU ZO   ZCWEZC FZ WOET BZ YWSSSSSBW    Z X M B B FBC  XSE FE<s> OF WCR WM BT ZYEZWSOU Z BCGTW X BXCW Z B BZM WCTBOCZBZT C G Z HN CTZWBF     WBZSE BSQX BBQXFE O  O DB Z N O W FYQ ZEZ EWCFWFYZ WO  C CYSFV FU EFCFFBCW Z SBDB B SY BZWSC BEZB WSQZ WSFUEZEHBFEO BMWBYOX BUSOWBS F B NC OYBEYOBBYB EC C BCM WDBNC XEBFBYB FBB BOG Z BMYN Z G  M BI ZWB MCNWBZX ED C<s>XQ BBEGSE BE BESB  B BE CB BUW C C BZWZBOWZW ZBOZ W UOOOOEB B  Z EBSFHT FT B CN YSB E X WBE CB SOVZ CO Z OT E B B O EB SECWU W B CZY BZT SY W BY BS Z W BBEQ BSEO BSEO BB XQ BBBB BZT B OMWY B Q  HDEDWQBZ QBSS  ZBOBOW BSQBFW B W  <s>OZ WUZB VB ZWZC CZ OBM B B BU Z Z C B FEBZOOD WE SYB MW V B ZB B B BXQ HBWEGCEZ H Z Q H V FY XV Z M FD BZ B ZV BWB R CB O N O T W BWSZCW EXBB WBZW SEYZ B GYZF O DBY N CWBZE WBWB SBDFBUSXC  B WE SCUZFGBFBEH STWBEQEBOX  F  B XBOEBQ TNCBV B HV ZB B BSBUWB WO I O OCEZBCZ BC W BFGM BZB Q E SBYBN QX  SBY XDY WZW F B  BZ ZTZ M ECBEG QB WY Z OWZDO  B<s> CZ ZGBZCZ BOQSC W WB ZB Z VHSCZSB NOCQWBM Z  CTBEC B M W YEHG FEF CSXB ZB B WFBO BDC ZFC CWB BDS EDBZ  FESBBCESB ESEZB'BX B O HB  QB GSB B D BN <s> COZ CB BYBXBX ZUZB C BYB W EYB O ZWM TF M M BZB SZDBSWZNQZ FBZ B CDSBEDWD OW XU YBZB CCC BOOXB X F X FOZEOBNMYZEXB Q YTZ O EMZ ECW BSBSS  WWOEXDI YZ EOZ WO YBBYQ O ZB B BZ MZ WFBOSZ UBUWBU Z FOB Q  DNZW SBZBYSX GBFBESNYC V B BZ S F EBCFB ZF'ST B ZBE ZB G X CBUW  W XDS BBW EBFB XBEGB BEB B E SUZU BEOB BC UE B EBOEBEPBCB BE BE F EBBEGSECBEOBUM B  B OF BE Z'CB Z\"}\n",
      "{'text': \"B ZVEGCBE BXB BBEMYBE TB  BX EG UZ UZGM <s>ZBG E B BCB EH  Y BE B OFBE UENOB B BCBESEZ EBEOBBEC WFXBF OUEMWB    BSBOWHBBB WF BB EGBBXBE BSOUOEOE FOH WB ZWDW QWZC DW EWEOZBDZZZOBSBQXB VNB S BZ BD B B EB BBUEBV O ESBT B ME EG F F ZCF  XXWDZY CZW CQYBKBT CB H Z ODCWZX BCEUZ OGBEB  Z W FBZBE  WWZWBU WSZ OZOBS ZFHBMOXQ CEHX O BS HXS'BU WSEB CBMB BVB SBESZ B B WWW CE YZOBHBZ BUBZ DB FBECBESBD EOBEB SUOE XOXDW WQ BBBSS OO Z OQ C WCFEHBZMHE FBW WD VCFZBN FC BZ<s>EBBEB Q B ND MOH BSYE O<s>MB XD CFCTBMBYBXB Z BFB TB CXWF HP O B MCSEDZZS WWYU B BOBO F F CXOXWWW SS WBBSEBBB ZUZ SXO W QW CSBWQ B ZWEBYM  CB BCDBZ W WB WBZBYSV XSZMYX  BDEBT BDMDM BOGZB EBUMB W SUBZ QB S H UC CEQ QSBFZB  B U BB B B CC SFD  <s>YBEGY M EZB TZBZB BEBXBW ON XBEB OZX BEZB BH SB B HWSEMB W CEBY B H BEFB XCXZ CX BX B BEGB B MBFBZDXY COBGB SMYB BTBZBTEZ CSYZ ZYEBYWSX WBZES BWB BUBE ZBCX B BX EZB BSEBEHEUOYA FYQG O OBGZBED BY EX ZSBW BZ CECBWSGZBZEWTB B EQBFW B SEBU<unk>NCB CE CUSCZSBEKM FBQ OEB B SB B BEH  <unk>FCX <s>N C BZ EBGBNVO W Z OD MNT Z VZO ZE BM ZO BC ZCFY\"}\n",
      "{'text': \"CZ  BEC GM FCBU BQZ BOB SBZCO Z YUE BUZ WU B ZEMOB CYWU OB ZBEI BXZR   U  BEWBBEZBEDB   BBE FBO B BSBBSCBWWFW ZB WZWZ DZW ZWCZB WZW OD B ZEC VC TBMWB BZ WSOFWB F ZTWBOBSBBBUS N V  BHCO B CBUBS E BQ BE BW Z  Z BG CXCX Z Z  SBMT TU    Z  E WZ BMWOCZ OUS WF XCM B XWZWC D C CWSES O C NC BWCBNU BC UWZG OT FXGB COB WB ZWWZ BWQ E BEC B WB WZ ZEHWZ SEDT OB CYCF UNE QBMYUBWZT NVGTBZH Z OBOU GB SG B O BZC EWZB BBCB CB B B B B BE BXZ E BEHBUCBEBZBVB X BYCB ZB TWOZ  EB BZWBZWWW B BZ BS<s>WB X S<s> BSZOCO W BDM X DO DZ  'E XW B <s>OWW  ZMY ZXW CUOXWB WSCB X OTZWFZM XBZOWNCBZWQF BBFD U YCU EB W MVF B S QBZBZ GT B B BBUCEZ WB OS W ZEZ TWZ WB GX B WBEBEWS WVZBZ <s>O ZE B BHEB XZWZ DY WOZ B MWBEZX S BMEUOZ OQBYF VFPOB  FB X SX B ZW XGSB WG BBBZ ZCZBB Z BY BZ SCWCBC S WQOX ZBTB EOBFVGQM F OBZ BSZHQ  CWB X EYTW ZT B BO MEB  DNZCYWBEHBEHO SBUEB SWEBE CB Z XOB ZCFZ O OZXMZ C<s>GQG GOEC WZOQB <unk>CZO B O OWS EFB OEZ BEOB B W HBEBU  BZZ BEWFOOB<s>EH OOQOXOXOXOXOOOX EDU BZBECB GOM WNUE F  BZ Q BDCG ZWBZ D ED B O ZWMW OFZ ZWZBZYHOB SBZ M O COUB BZW B W BWH EOCOEZW QFGBE  W ZWZBZOZBSBWWBSBB  XFE WWZUEVEGW  ZZFQ UZO C S ZYFB DBMXCOYB CZ W Q  ZBM  ZB X BUW BZBE B Z B FTZBT B WBEZ NB FM T OGTOGBFB BMWSZ WSU CBZBECB B C BXZEQ BMO M X BOZU CWY MO E CAFCBE B  Z C FCESB B BE E B  F BEB  B SB BZBXSBEZBE BX B BO BFX BEC EOEYHN BF  OZW OBZBWOSBEZWZ ZO Q SSWZ DOB C B OB C C CGO YB ECWGBZWBOQWZWFWGS GBWZ XZSCZS X E WCSZWS    ZBWXWZ ZD MZ  DBXBZ  ZDC BE C ZBCBW B QUBECZBZ F BQ OH X WEOB S FMCZ ECB<s>FZOBZ BB C B ZO X DQGQ Q Z CQOSMW ZEG WWBU Z NOZEWBMQOC' C MWZ O B  B ZOBUOZB  BG EU  YBO BS FBZZFBMQ BBEBU B  BE BU E B BE BBEGBETZBSB\"}\n",
      "{'text': 'E E YC GRWB VHNM YB  Z ONOZC T BO B BF   T OZBO WZYB YMWZ Z E XDGNOYO BZCW Z B BT BU MB BCBOB OZZB E BZ FCD T ESCYB CFSCWU B  B H Z ZOW YZ B Z BZWZWFBE FS  CUBYMF BECBSBY O BY BX BEZ YBZ O S  WBE WS Z ZBU BETB OYN CO W PZ TW T Z Z Z OZZWOWEDZXZEDZXF WCZ CZ XZ BZCU EQC  YTMOA<unk> U U ZBTWSBU B EB BEBECBUOB ZBB CWCM BWS HY EZ BECBD CBWB QEDWC W B SN  S CES BCSFBOWBS BZ T UB EBU CBXW BCTFZBDSZ D XWCZ CZU DZ DZY CDZ CZ CZW ZX CBZWFOZB CQB ZSZBS W EBBCBSECQZ BB B WZ WOEWCZ CB B ZXSBZW B CBW EBT  BYBZ BUZ BV ZBT B M Y CW TWCBZ BXBUMZ OWXBEB  B B B B E BEBESB WB B  E B B EYBB SEY B B EEMW WW BOOBDZDZD CWSSUSO ZTS W B CM ED BUXECZB OHZ HSB OUCFB B MF F V CH G UBOW BO WB B OZBE BE B BBE B B  B CB ECBEB B B B B BFZWWW   F OOOSSOBE X OZW ZY GSBSYBOME OW VFYB Z <s> Z MZF  WBZOZWSEB B ZBYBFSFBBBBBE BOB BBB  WF XZ UF CBEB SB BBEFBEF BE BB BE BE B COE S EBE WWBE BEB BE B BESBE B O E BU'}\n",
      "{'text': \"BED B  DECZ ZGR EO FOC ZOBP ZCG<s> FTHOWME WZ  ZDOQNCFGLSCZ T B FHNOBV TO U O CBE BT BOBE G  EBCBH H ZSCBH ZS OBVZCE BEWBYCB C O TBFE EHT S B B B XOXZW B CHT BF WB QT O O Z B FB EZX SS B QXFEBWZT BSUZ BBBQ QF WZOHS WCF BCF BWYB TE C B U DEC XWBSBWWWBSSSSBBB  FBCBZ  QZSXMBF WZ VZ C B E OKWCBZEZWYMH W Z S EOBSEBSEBEHB BQBUGZUYB  BT OOY M W B O WWOEZ TB B X MODE BM B H YBOZBZWEC X CB BECNS FZ CZ QB BWZ EBBWZ WB HWBSET SOYCE ZY OB B W B EOEO CXOXGXG G BT QTZBC B WYFXWOZB F OZBW Z D ZWY Y  BMYBZ ZFBSF QBMBBZCSS E SWNBF QEFNQMSG<s>Z </s> WBSZFG W ZZW B SMTWZ WMBSE CRYOTWOX CV WZ BXOUZ BBZWZWWS CX<s> BUSEE ZE OBX<s>WB WBB<s>EGB BEH S ZW BB BB  E WBSOQXFE BSSEC BSFW ZQ'W BB BBB ZWBZOEFO E B HEMB BQWSH SEOBSEBCBX H OSOX<s>WBSEOWU BZB B O F COHC WEBYMZBBSSWWBBSWF BO WBB WB X BXFB BUFBSSEUSEOEO ED WMBNB CNZWP B W F E  YEQHTE HFEZ   B Q B Z WB WBUCB B OBN FOSCWSWGBHWZF BT WNG CB FBUE BHBECBBMEOEZ CB B ZM WB Z  CZBM RB BFZBZSSZ SEQWO B N B C BGO  BEHB E E B B  YS H F ZX W W BYBOBBZBZ  S Y WESBQ WB ESNCF B SQEC B BTWBEC B B MMFYCB BEZEHOF OMH CZO O EY Q 'ZGSFN E Z <s>ZOZ DCM NCBCO OD EYNBC S O GQMCBNFC GD E FN SMMEU F BEZCMNDBU UMBOBEHZX HB HBXOEBBEGCBZU BEPQ S TB  BOE BY  WF SY  SYSZ OCESBSXO BSW SCX XFBSEO BSE BBXOWBSEQ BBEO F BBBBZBWBE O WQBZ DZWO XSZ BBZWRUH MBOCFU B WBZ STW BZWSEQB C BZQ XSU BB GT E N Q ZQ BBCZUZW BYX MFEGFUOBM  B C XEOF BFZFO X OF BTBSEBET HBE BEQ'G B S WBZY BZB B ZU QWC UEGHDOEFB QBFGQZ OBZ CS HMR HMZWS TWS TB WXZ S CY B WTWQ BZ TWYOWZSBZ XY CSE ZU   CVZ Z BNW W BC W OHD RXMB C OB OX  E ZECBXOB B  BE B CWZGCOQWZ ZSZWB ZZUN WZ YMOGB O B MBZ<s>OZOW WYS GNGXCBX Z OTZCB  EB BCT C CSEQ BE BEHMECBEH U B TZECE SZ WFETWBOT B HWXDSWCZECKOY E P ZB W COYWB BMC XEDWBCSMBZB BWF ECOEHQWB O CF U CMB BZQ WSZX YZBWBQS Y T CE BNSUBVWFY  ZSDZWOZ Z ZWBBDW Q EC WCBY QSB BE  QB B  WYWYZGW   WM M B CO VBWO B BZWO BMBO T BT  O WCQB B C  </s>FF SH BO  ZBBNH VEZ F BE B OXZOF EOWM QF  ZMCQ WB OB BE BEO O  T B EDXZOZGEFYB ZO GWBMW WZ BEDBBEZE T O CB YB SOFB W BF C U S M BZX  SW W BN O Y  EN W O QBZB V VEUOZBS SDSFBF'FE<s>EZBZ CFOY FCFBCX BOWFTMB SBYBYZT FOS B<s>EBBBTUZGF FGBBEBSYOOXFW CECECEF  Z DWEFSB SZTBHT C EBZ BCE B OZH WF BSSXOWFB BEHB S BSE EWZ  ZBZWDWD B B BSBSBB  EDS  BNBZEC WOW WC Y  CZ CZX FOZ FBZ WFCZ DH UEDWECSTV X T B CBD C QB WBD  OC SBEB  BEDW EBDW BZGUF CZ SNEZ OBFGG U<s>CVCYZBEBXUE</s>QBU V BM ZO Q ZC ZEOX C SZWYC B BZMS ZTQ<s> BEB M OE BOE  U OX      WB OOXWPX WFBY ZBYOXBXOXHEQW BOZB ZWFWZOBCY W SOBZ SZWOZ H X EMV Q OBEBZBSBWP BWZBO BESUESZ'EOB GHZCN  UM  BE WB CM B XMGWOWWV   X X  CV G C M MWMWY ZYOS Y WUG T OT B B ZEHXBBO E TZTOSOB XHBTG O E  X W WB</s>XMCEZB <s>EZB CE BO <unk> BEM O Z BGBODH W EESSEIZB TETYMO ZWEXE N HNM T OBE BOXOE BBSQZZZBWEGBYB B EEBHM GB O O EBY ZSW C BV WQU O HXF YB WW UB FG BOZOWZ DBZ EOEZBZ G E<s>BG CBS BMEWZN B B CZ B QWZBX WYBM ODB BFZFOBS OX  YBBZWCF F O O OXOWF  ZBBE U BFBEZB BZSOSBBFB B  W B BFWBSFZW EB BSE MW S F COWZ F WC WBZT S BXST B BBMWQM SZ S OE B QB VX C B BS BHWEB OSBEG BOB BE B O OW S MNCWECSWY W W CMWY </s>C B C YZ OZF OZBM   DY T EDUEDWZ O ZSBBNBFZUF BEZ F O EWL QCB CBZEBZWZC  FO CF STWZTWS SFBSS SF C BYB ZCYABZY U TYE WF   WSEOB SV UE OEZ B U WBE BDBX Z CB Z CWZ SWBOY BCF ZOW W CY Z WYMBZ ZOB BEB WS Z QX B YWWZB X BB CFOC ZUW B S  BUCWSE EZ MZOSOECO ZY ZY SZB  B SBT T SB  XEGBMCBE B BEB BE B EBEB  ZE BEH  B B W EC USB E B 'B\"}\n"
     ]
    }
   ],
   "source": [
    "# KeyDataset is a util that will just output the item we're interested in.\n",
    "pipe = pipeline(model=\"hf-internal-testing/tiny-random-wav2vec2\")\n",
    "dataset = load_dataset(\"hf-internal-testing/librispeech_asr_dummy\", \"clean\", split=\"validation[:10]\")\n",
    "\n",
    "for out in pipe(KeyDataset(dataset, \"audio\")):\n",
    "    print(out)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'sequence': 'I have a problem with my iphone that needs to be resolved asap!!',\n",
       " 'labels': ['urgent', 'phone', 'computer', 'not urgent', 'tablet'],\n",
       " 'scores': [0.5036367177963257,\n",
       "  0.47879841923713684,\n",
       "  0.012600354850292206,\n",
       "  0.002655796706676483,\n",
       "  0.0023087686859071255]}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### text pipeline\n",
    "# This model is a `zero-shot-classification` model.\n",
    "# It will classify text, except you are free to choose any label you might imagine\n",
    "classifier = pipeline(model=\"facebook/bart-large-mnli\")\n",
    "classifier(\n",
    "    \"I have a problem with my iphone that needs to be resolved asap!!\",\n",
    "    candidate_labels=[\"urgent\", \"not urgent\", \"phone\", \"tablet\", \"computer\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'score': 0.8941310048103333, 'answer': '$154.06', 'start': 74, 'end': 74}]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### multi-modal pipeline\n",
    "vqa = pipeline(model=\"impira/layoutlm-document-qa\")\n",
    "vqa(\n",
    "    image=\"https://huggingface.co/spaces/impira/docquery/resolve/2359223c1837a7587402bda0f2643382a6eefeab/invoice.png\",\n",
    "    # question=\"What is the invoice number?\",\n",
    "    question=\"What is the total amount on the invoice?\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.9.6 ('.venv': venv)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
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