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updating listing file with three v2 sparse model (#412)
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* updating listing file with three v2 sparse model

Signed-off-by: Dhrubo Saha <[email protected]>

* adding changelog

Signed-off-by: Dhrubo Saha <[email protected]>

---------

Signed-off-by: Dhrubo Saha <[email protected]>
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dhrubo-os authored Aug 8, 2024
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1 change: 1 addition & 0 deletions CHANGELOG.md
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Expand Up @@ -43,6 +43,7 @@ Inspired from [Keep a Changelog](https://keepachangelog.com/en/1.0.0/)
- Update model upload history - opensearch-project/opensearch-neural-sparse-encoding-doc-v2-mini (v.1.0.0)(TORCH_SCRIPT) by @dhrubo-os ([#407](https://github.com/opensearch-project/opensearch-py-ml/pull/407))
- Update model upload history - opensearch-project/opensearch-neural-sparse-encoding-doc-v2-distill (v.1.0.0)(TORCH_SCRIPT) by @dhrubo-os ([#405](https://github.com/opensearch-project/opensearch-py-ml/pull/405))
- Update model upload history - opensearch-project/opensearch-neural-sparse-encoding-v2-distill (v.1.0.0)(TORCH_SCRIPT) by @dhrubo-os ([#410](https://github.com/opensearch-project/opensearch-py-ml/pull/410))
- updating listing file with three v2 sparse model - by @dhrubo-os ([#412](https://github.com/opensearch-project/opensearch-py-ml/pull/412))

### Fixed
- Fix the wrong input parameter for model_uploader's base_download_path in jekins trigger.([#402](https://github.com/opensearch-project/opensearch-py-ml/pull/402))
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"description": "The model can be used for Information Retrieval: Given a query, encode the query will all possible passages (e.g. retrieved with ElasticSearch). Then sort the passages in a decreasing order."
}
}
},
{
"name": "amazon/neural-sparse/opensearch-neural-sparse-encoding-doc-v2-distill",
"versions": {
"1.0.0": {
"format": [
"torch_script"
],
"description": "This is a neural sparse encoding model: It transfers text into sparse vector, and then extract nonzero index and value to entry and weights. It serves only in ingestion and customer should use tokenizer model in query."
}
}
},
{
"name": "amazon/neural-sparse/opensearch-neural-sparse-encoding-doc-v2-mini",
"versions": {
"1.0.0": {
"format": [
"torch_script"
],
"description": "This is a neural sparse encoding model: It transfers text into sparse vector, and then extract nonzero index and value to entry and weights. It serves only in ingestion and customer should use tokenizer model in query."
}
}
},
{
"name": "amazon/neural-sparse/opensearch-neural-sparse-encoding-v2-distill",
"versions": {
"1.0.0": {
"format": [
"torch_script"
],
"description": "This is a neural sparse encoding model: It transfers text into sparse vector, and then extract nonzero index and value to entry and weights. It serves in both ingestion and search."
}
}
}
]

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