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Add Python ML examples to the API docs (#2489)
Co-authored-by: Quentin Pradet <[email protected]>
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‎docs/examples/095e3f21941a9cc75f398389a075152d.asciidoc

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// ml/trained-models/apis/infer-trained-model.asciidoc:1043
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[source, python]
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----
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resp = client.ml.infer_trained_model(
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model_id="cross-encoder__ms-marco-tinybert-l-2-v2",
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body={
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"docs": [
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{
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"text_field": "Berlin has a population of 3,520,031 registered inhabitants in an area of 891.82 square kilometers."
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},
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{
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"text_field": "New York City is famous for the Metropolitan Museum of Art."
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},
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],
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"inference_config": {
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"text_similarity": {"text": "How many people live in Berlin?"}
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},
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},
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)
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print(resp)
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----

‎docs/examples/0e5d25c7bb738c42d471020d678e2966.asciidoc

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// ml/trained-models/apis/start-trained-model-deployment.asciidoc:173
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[source, python]
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----
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resp = client.ml.start_trained_model_deployment(
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model_id="my_model",
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deployment_id="my_model_for_ingest",
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wait_for="started",
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timeout="1m",
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)
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print(resp)
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----

‎docs/examples/147d341cb212dcc015c129a9c5dcf9c9.asciidoc

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// ml/trained-models/apis/put-trained-models-aliases.asciidoc:82
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[source, python]
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----
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resp = client.ml.put_trained_model_alias(
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model_id="flight-delay-prediction-1574775339910",
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model_alias="flight_delay_model",
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)
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print(resp)
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----

‎docs/examples/2d633b7f346b828d01f923ce9dbf6ad5.asciidoc

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// ml/trained-models/apis/put-trained-model-vocabulary.asciidoc:63
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[source, python]
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----
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resp = client.ml.put_trained_model_vocabulary(
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model_id="elastic__distilbert-base-uncased-finetuned-conll03-english",
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body={"vocabulary": ["[PAD]", "[unused0]", ...]},
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)
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print(resp)
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----

‎docs/examples/35a272df8c919a12d7c3106a18245748.asciidoc

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// ml/trained-models/apis/infer-trained-model.asciidoc:849
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[source, python]
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----
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resp = client.ml.infer_trained_model(
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model_id="lang_ident_model_1",
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body={
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"docs": [
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{
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"text": "The fool doth think he is wise, but the wise man knows himself to be a fool."
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}
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]
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},
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)
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print(resp)
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----

‎docs/examples/3c345feb7c52fd54bcb5d5505fd8bc3b.asciidoc

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// ml/trained-models/apis/infer-trained-model.asciidoc:1008
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[source, python]
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----
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resp = client.ml.infer_trained_model(
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model_id="model2",
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body={
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"docs": [{"text_field": "<long text to extract answer>"}],
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"inference_config": {
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"question_answering": {"question": "<question to be answered>"}
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},
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},
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)
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print(resp)
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----

‎docs/examples/4c174e228b6b74497b73ef2be80de7ad.asciidoc

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// ml/trained-models/apis/get-trained-models.asciidoc:1460
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[source, python]
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----
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resp = client.ml.get_trained_models()
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print(resp)
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----

‎docs/examples/5837d5f50665ac0a26181d3aaeb3f204.asciidoc

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// ml/trained-models/apis/start-trained-model-deployment.asciidoc:181
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[source, python]
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----
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resp = client.ml.start_trained_model_deployment(
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model_id="my_model",
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deployment_id="my_model_for_search",
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)
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print(resp)
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----

‎docs/examples/776b553df0e507c96dbdbaedecaca0cc.asciidoc

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// ml/trained-models/apis/infer-trained-model.asciidoc:880
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[source, python]
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----
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resp = client.ml.infer_trained_model(
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model_id="model2",
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body={"docs": [{"text_field": "The movie was awesome!!"}]},
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)
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print(resp)
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----

‎docs/examples/7e4cb3de3e3c75646b60f9f81ddc59cc.asciidoc

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// ml/trained-models/apis/clear-trained-model-deployment-cache.asciidoc:43
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[source, python]
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----
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resp = client.ml.clear_trained_model_deployment_cache(
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model_id="elastic__distilbert-base-uncased-finetuned-conll03-english",
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)
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print(resp)
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----

‎docs/examples/821422f8a03dc98d024a15fc737fe9eb.asciidoc

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// ml/trained-models/apis/delete-trained-models-aliases.asciidoc:51
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[source, python]
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----
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resp = client.ml.delete_trained_model_alias(
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model_id="flight-delay-prediction-1574775339910",
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model_alias="flight_delay_model",
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)
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print(resp)
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----

‎docs/examples/9225841fdcddaf83ebdb90c2b0399e20.asciidoc

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// ml/trained-models/apis/get-trained-models-stats.asciidoc:405
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[source, python]
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----
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resp = client.ml.get_trained_models_stats()
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print(resp)
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----

‎docs/examples/9cbb097e5498a9fde39e3b1d3b62a4d2.asciidoc

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// ml/trained-models/apis/infer-trained-model.asciidoc:945
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[source, python]
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----
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resp = client.ml.infer_trained_model(
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model_id="model2",
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body={
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"docs": [{"text_field": "This is a very happy person"}],
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"inference_config": {
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"zero_shot_classification": {
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"labels": ["glad", "sad", "bad", "rad"],
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"multi_label": False,
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}
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},
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},
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)
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print(resp)
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----

‎docs/examples/aa6282d4bc92c753c4bd7a5b166abece.asciidoc

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// ml/trained-models/apis/start-trained-model-deployment.asciidoc:133
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[source, python]
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----
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resp = client.ml.start_trained_model_deployment(
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model_id="elastic__distilbert-base-uncased-finetuned-conll03-english",
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wait_for="started",
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timeout="1m",
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)
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print(resp)
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----

‎docs/examples/be6b0bfcdce1ef100af89f74da5d4748.asciidoc

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// ml/trained-models/apis/put-trained-model-definition-part.asciidoc:64
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[source, python]
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----
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resp = client.ml.put_trained_model_definition_part(
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model_id="elastic__distilbert-base-uncased-finetuned-conll03-english",
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part="0",
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body={
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"definition": "...",
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"total_definition_length": 265632637,
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"total_parts": 64,
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},
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)
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print(resp)
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----

‎docs/examples/cc90639f2e65bd89cb73296cac6135cf.asciidoc

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// ml/trained-models/apis/delete-trained-models.asciidoc:54
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[source, python]
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----
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resp = client.ml.delete_trained_model(
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model_id="regression-job-one-1574775307356",
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)
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print(resp)
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----

‎docs/examples/cee491dd0a8d10ed0cb11a2faa0c99f0.asciidoc

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// ml/trained-models/apis/infer-trained-model.asciidoc:1078
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[source, python]
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----
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resp = client.ml.infer_trained_model(
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model_id="model2",
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body={
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"docs": [
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{
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"text_field": "The Amazon rainforest covers most of the Amazon basin in South America"
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}
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],
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"inference_config": {
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"ner": {"tokenization": {"bert": {"truncate": "first"}}}
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},
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},
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)
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print(resp)
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----

‎docs/examples/d50b030edfe6d1128eb76aa5ba9d4e27.asciidoc

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// ml/trained-models/apis/put-trained-models-aliases.asciidoc:94
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[source, python]
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----
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resp = client.ml.put_trained_model_alias(
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model_id="flight-delay-prediction-1580004349800",
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model_alias="flight_delay_model",
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reassign="true",
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)
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print(resp)
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----

‎docs/examples/dbf93d02ab86a09929a21232b19709cc.asciidoc

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// ml/trained-models/apis/stop-trained-model-deployment.asciidoc:67
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[source, python]
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----
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resp = client.ml.stop_trained_model_deployment(
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model_id="my_model_for_search",
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)
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print(resp)
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----

‎docs/examples/ff776c0fccf93e1c7050f7cb7efbae0b.asciidoc

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// ml/trained-models/apis/infer-trained-model.asciidoc:905
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[source, python]
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----
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resp = client.ml.infer_trained_model(
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model_id="model2",
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body={
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"docs": [{"text_field": "Hi my name is Josh and I live in Berlin"}]
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},
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)
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print(resp)
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----

‎utils/generate-examples.py

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"inference/delete-inference.asciidoc",
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"inference/post-inference.asciidoc",
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"inference/put-inference.asciidoc",
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"ml/trained-models/apis/clear-trained-model-deployment-cache.asciidoc",
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"ml/trained-models/apis/delete-trained-models-aliases.asciidoc",
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"ml/trained-models/apis/delete-trained-models.asciidoc",
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"ml/trained-models/apis/get-trained-models-stats.asciidoc",
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"ml/trained-models/apis/get-trained-models.asciidoc",
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"ml/trained-models/apis/infer-trained-model-deployment.asciidoc",
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"ml/trained-models/apis/infer-trained-model.asciidoc",
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"ml/trained-models/apis/put-trained-model-definition-part.asciidoc",
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"ml/trained-models/apis/put-trained-model-vocabulary.asciidoc",
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"ml/trained-models/apis/put-trained-models-aliases.asciidoc",
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"ml/trained-models/apis/put-trained-models.asciidoc",
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"ml/trained-models/apis/start-trained-model-deployment.asciidoc",
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"ml/trained-models/apis/stop-trained-model-deployment.asciidoc",
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"ml/trained-models/apis/update-trained-model-deployment.asciidoc",
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]
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