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add text embedding API example doc #710

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merged 2 commits into from
Jan 25, 2023

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ylwu-amzn
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Signed-off-by: Yaliang Wu [email protected]

Description

Add text embedding API example doc

Issues Resolved

[List any issues this PR will resolve]

Check List

  • New functionality includes testing.
    • All tests pass
  • New functionality has been documented.
    • New functionality has javadoc added
  • Commits are signed per the DCO using --signoff

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.
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@ylwu-amzn ylwu-amzn requested a review from a team January 25, 2023 01:25
rbhavna
rbhavna previously approved these changes Jan 25, 2023
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codecov-commenter commented Jan 25, 2023

Codecov Report

Merging #710 (db760fd) into 2.x (1ba4de8) will not change coverage.
The diff coverage is n/a.

@@            Coverage Diff            @@
##                2.x     #710   +/-   ##
=========================================
  Coverage     84.34%   84.34%           
  Complexity     1052     1052           
=========================================
  Files            99       99           
  Lines          3833     3833           
  Branches        352      352           
=========================================
  Hits           3233     3233           
  Misses          450      450           
  Partials        150      150           
Flag Coverage Δ
ml-commons 84.34% <ø> (ø)

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Impacted Files Coverage Δ
...n/java/org/opensearch/ml/cluster/MLSyncUpCron.java 84.41% <ø> (ø)

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We can trace this example model [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) to torchscript with two options:

## 1.1 trace sentence transformers model
If you have [`sentence-transformers`](https://pypi.org/project/sentence-transformers/) installed. You can trace this model directly: `SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')`.
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I don't think model = SentenceTransformer('all-MiniLM-L6-v2') will trace the model.

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how about:

If you have sentence-transformers installed. You can save this model directly: SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2') and then trace the model using torchScipt.

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Sure, sounds good

dhrubo-os
dhrubo-os previously approved these changes Jan 25, 2023
Signed-off-by: Yaliang Wu <[email protected]>
@ylwu-amzn ylwu-amzn dismissed stale reviews from dhrubo-os and rbhavna via 148c587 January 25, 2023 01:58
@ylwu-amzn ylwu-amzn merged commit 3992d93 into opensearch-project:2.x Jan 25, 2023
@ylwu-amzn ylwu-amzn added the documentation Improvements or additions to documentation label Jan 31, 2023
ylwu-amzn added a commit to ylwu-amzn/ml-commons that referenced this pull request Feb 17, 2023
* add text embedding API example doc

Signed-off-by: Yaliang Wu <[email protected]>

* address comment

Signed-off-by: Yaliang Wu <[email protected]>

Signed-off-by: Yaliang Wu <[email protected]>
ylwu-amzn added a commit to ylwu-amzn/ml-commons that referenced this pull request Mar 3, 2023
* add text embedding API example doc

Signed-off-by: Yaliang Wu <[email protected]>

* address comment

Signed-off-by: Yaliang Wu <[email protected]>

Signed-off-by: Yaliang Wu <[email protected]>
ylwu-amzn added a commit to ylwu-amzn/ml-commons that referenced this pull request Mar 3, 2023
* add text embedding API example doc

Signed-off-by: Yaliang Wu <[email protected]>

* address comment

Signed-off-by: Yaliang Wu <[email protected]>

Signed-off-by: Yaliang Wu <[email protected]>
ylwu-amzn added a commit to ylwu-amzn/ml-commons that referenced this pull request Mar 3, 2023
* add text embedding API example doc

Signed-off-by: Yaliang Wu <[email protected]>

* address comment

Signed-off-by: Yaliang Wu <[email protected]>

Signed-off-by: Yaliang Wu <[email protected]>
ylwu-amzn added a commit that referenced this pull request Mar 4, 2023
* add text embedding API example doc

Signed-off-by: Yaliang Wu <[email protected]>

* address comment

Signed-off-by: Yaliang Wu <[email protected]>

Signed-off-by: Yaliang Wu <[email protected]>
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5 participants