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Updated asr inference sample score, online and batch endpoint notebooks #2441

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Jul 24, 2023
Merged

Updated asr inference sample score, online and batch endpoint notebooks #2441

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62dde2c
Updated asr inference sample score, online and batch endpoint notebooks
tanmaybansal104 Jul 11, 2023
3205a87
Merge remote-tracking branch 'origin/main' into tanmaybansal/asr-note…
tanmaybansal104 Jul 14, 2023
a5019bc
Updated openai whisper model from 8 to 10 in the batch deployment not…
tanmaybansal104 Jul 17, 2023
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5 changes: 2 additions & 3 deletions .../foundation-models/system/inference/automatic-speech-recognition/asr-batch-endpoint.ipynb
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Expand Up @@ -19,7 +19,6 @@
"We will use the [Librispeech ASR](https://huggingface.co/datasets/librispeech_asr/viewer/clean/test) dataset. \\\n",
"You can use also use custom audio files stored on the cloud and verify inference.\n",
"- Most common audio formats (m4a, wav, flac, wma, mp3, etc.) are supported.\n",
"- The whisper model can process only 30 seconds of data at a time, so if the file you upload is longer than 30 seconds, only the first 30 seconds will be transcribed. This can be circumvented by splitting the file into 30 second chunks.\n",
"\n",
"### Outline\n",
"* Set up pre-requisites.\n",
Expand Down Expand Up @@ -138,7 +137,7 @@
"compute_cluster = AmlCompute(\n",
" name=compute_name,\n",
" description=\"An AML compute cluster\",\n",
" size=\"Standard_DS4_V2\",\n",
" size=\"Standard_DS5_V2\",\n",
" min_instances=0,\n",
" max_instances=3,\n",
" idle_time_before_scale_down=120,\n",
Expand All @@ -164,7 +163,7 @@
"outputs": [],
"source": [
"model_name = \"openai-whisper-large\"\n",
"model_version = \"4\"\n",
"model_version = \"10\"\n",
"foundation_model = registry_ml_client.models.get(model_name, model_version)\n",
"print(\n",
" f\"Using model name: {foundation_model.name}, version: {foundation_model.version}, id: {foundation_model.id} for inferencing.\"\n",
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5 changes: 2 additions & 3 deletions ...foundation-models/system/inference/automatic-speech-recognition/asr-online-endpoint.ipynb
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Expand Up @@ -19,7 +19,6 @@
"We will use custom audio files that have been uploaded to the cloud. \\\n",
"You can replace the links with any audio file stored on the cloud and verify inference.\n",
"- Most common audio formats (m4a, wav, flac, wma, mp3, etc.) are supported.\n",
"- The whisper model can process only 30 seconds of data at a time, so if the file you upload is longer than 30 seconds, only the first 30 seconds will be transcribed. This can be circumvented by splitting the file into 30 second chunks.\n",
"\n",
"### Outline\n",
"* Set up pre-requisites.\n",
Expand Down Expand Up @@ -149,10 +148,10 @@
" name=\"demo\",\n",
" endpoint_name=online_endpoint_name,\n",
" model=foundation_model.id,\n",
" instance_type=\"Standard_DS4_v2\",\n",
" instance_type=\"Standard_DS5_v2\",\n",
" instance_count=1,\n",
" request_settings=OnlineRequestSettings(\n",
" request_timeout_ms=60000,\n",
" request_timeout_ms=90000,\n",
" ),\n",
")\n",
"workspace_ml_client.online_deployments.begin_create_or_update(demo_deployment).wait()\n",
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4 changes: 2 additions & 2 deletions ...ion-models/system/inference/automatic-speech-recognition/sample-request/sample_score.json
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@@ -1,6 +1,6 @@
{
"inputs": {
"audio": ["https://huggingface.co/datasets/Narsil/asr_dummy/resolve/main/1.flac", "https://audiovisionfiles.blob.core.windows.net/audio/audio.m4a"],
"language": ["en", "en"]
"audio": ["https://datasets-server.huggingface.co/assets/librispeech_asr/--/all/train.clean.100/84/audio/audio.mp3"],
"language": ["en"]
}
}
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