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get-ml-model-bert-large-squad

Automatically generated README for this automation recipe: get-ml-model-bert-large-squad

Category: AI/ML models

License: Apache 2.0

  • CM meta description for this script: _cm.json
  • Output cached? True

Reuse this script in your project

Install MLCommons CM automation meta-framework

Pull CM repository with this automation recipe (CM script)

cm pull repo mlcommons@cm4mlops

cmr "get ml-model raw bert bert-large bert-squad language language-processing" --help

Run this script

Run this script via CLI
cm run script --tags=get,ml-model,raw,bert,bert-large,bert-squad,language,language-processing[,variations]
Run this script via CLI (alternative)
cmr "get ml-model raw bert bert-large bert-squad language language-processing [variations]"
Run this script from Python
import cmind

r = cmind.access({'action':'run'
              'automation':'script',
              'tags':'get,ml-model,raw,bert,bert-large,bert-squad,language,language-processing'
              'out':'con',
              ...
              (other input keys for this script)
              ...
             })

if r['return']>0:
    print (r['error'])
Run this script via Docker (beta)
cm docker script "get ml-model raw bert bert-large bert-squad language language-processing[variations]"

Variations

  • No group (any combination of variations can be selected)

    Click here to expand this section.

    • _onnxruntime
    • _tensorflow

  • Group "download-source"

    Click here to expand this section.

    • _amazon-s3
    • _armi
    • _custom-url.#
      • ENV variables:
        • CM_PACKAGE_URL: #
    • _github
    • _zenodo

  • Group "framework"

    Click here to expand this section.

    • _deepsparse
      • ENV variables:
        • CM_ML_MODEL_FRAMEWORK: deepsparse
        • CM_ML_MODEL_INPUT_IDS_NAME: input_ids
        • CM_ML_MODEL_INPUT_MASK_NAME: input_mask
        • CM_ML_MODEL_INPUT_SEGMENTS_NAME: segment_ids
        • CM_ML_MODEL_OUTPUT_END_LOGITS_NAME: output_end_logits
        • CM_ML_MODEL_OUTPUT_START_LOGITS_NAME: output_start_logits
    • _onnx (default)
      • ENV variables:
        • CM_ML_MODEL_FRAMEWORK: onnx
        • CM_ML_MODEL_INPUT_IDS_NAME: input_ids
        • CM_ML_MODEL_INPUT_MASK_NAME: input_mask
        • CM_ML_MODEL_INPUT_SEGMENTS_NAME: segment_ids
        • CM_ML_MODEL_OUTPUT_END_LOGITS_NAME: output_end_logits
        • CM_ML_MODEL_OUTPUT_START_LOGITS_NAME: output_start_logits
    • _pytorch
      • ENV variables:
        • CM_ML_MODEL_FRAMEWORK: pytorch
        • CM_ML_MODEL_INPUT_IDS_NAME: input_ids
        • CM_ML_MODEL_INPUT_MASK_NAME: input_mask
        • CM_ML_MODEL_INPUT_SEGMENTS_NAME: segment_ids
        • CM_ML_MODEL_OUTPUT_END_LOGITS_NAME: output_end_logits
        • CM_ML_MODEL_OUTPUT_START_LOGITS_NAME: output_start_logits
    • _tf
      • ENV variables:
        • CM_ML_MODEL_FRAMEWORK: tf
        • CM_ML_MODEL_INPUT_IDS_NAME: input_ids
        • CM_ML_MODEL_INPUT_MASK_NAME: input_mask
        • CM_ML_MODEL_INPUT_SEGMENTS_NAME: segment_ids
        • CM_ML_MODEL_OUTPUT_END_LOGITS_NAME: output_end_logits
        • CM_ML_MODEL_OUTPUT_START_LOGITS_NAME: output_start_logits

  • Group "packing"

    Click here to expand this section.

    • _packed
      • ENV variables:
        • CM_ML_MODEL_BERT_PACKED: yes
    • _unpacked (default)
      • ENV variables:
        • CM_ML_MODEL_BERT_PACKED: no

  • Group "precision"

    Click here to expand this section.

    • _fp32 (default)
      • ENV variables:
        • CM_ML_MODEL_PRECISION: fp32
    • _int8
      • ENV variables:
        • CM_ML_MODEL_PRECISION: int8
        • CM_ML_MODEL_QUANTIZED: yes
Default variations

_fp32,_onnx,_unpacked

Native script being run

No run file exists for Windows

Script output

cmr "get ml-model raw bert bert-large bert-squad language language-processing [variations]"  -j