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

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- 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))
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- 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))
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- 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))
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- updating listing file with three v2 sparse model - by @dhrubo-os ([#412](https://github.com/opensearch-project/opensearch-py-ml/pull/412))
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### Fixed
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- 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))

utils/model_uploader/model_listing/pretrained_models_all_versions.json

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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."
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}
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}
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},
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{
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"name": "amazon/neural-sparse/opensearch-neural-sparse-encoding-doc-v2-distill",
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"versions": {
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"1.0.0": {
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"format": [
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"torch_script"
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],
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"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."
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}
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}
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},
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{
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"name": "amazon/neural-sparse/opensearch-neural-sparse-encoding-doc-v2-mini",
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"versions": {
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"1.0.0": {
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"format": [
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"torch_script"
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],
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"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."
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}
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}
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},
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{
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"name": "amazon/neural-sparse/opensearch-neural-sparse-encoding-v2-distill",
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"versions": {
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"1.0.0": {
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"format": [
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"torch_script"
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],
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"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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}
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}
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}
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]

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