Update Pretrained Model Listing - 2025-10-21 11:15:33

CHANGELOG.md

@@ -37,6 +37,7 @@ Inspired from [Keep a Changelog](https://keepachangelog.com/en/1.0.0/)
 - Upgrade numpy and python version ([#562](https://github.com/opensearch-project/opensearch-py-ml/pull/562))
 - Update space type mapping for sentence transformer models ([#574](https://github.com/opensearch-project/opensearch-py-ml/pull/574))
 - Update semantic highlighting sagemaker endpoint deploy scripts ([#585](https://github.com/opensearch-project/opensearch-py-ml/pull/585))
+- Update pretrained_models_all_versions.json (2025-10-21 11:15:33) by @nathaliellenaa ([#586](https://github.com/opensearch-project/opensearch-py-ml/pull/586))
 
 ### Fixed
 - Fix for uploading models with function_name instead of model_task ([#553](https://github.com/opensearch-project/opensearch-py-ml/pull/553))

utils/model_uploader/model_listing/pretrained_models_all_versions.json

@@ -264,71 +264,5 @@
         "description": "This is a sentence-transformers model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search."
       }
     }
-  },
-  {
-    "name": "amazon/neural-sparse/opensearch-neural-sparse-encoding-doc-v1",
-    "versions": {
-      "1.0.1": {
-        "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-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."
-      }
-    }
-  },
-  {
-    "name": "amazon/neural-sparse/opensearch-neural-sparse-encoding-doc-v3-gte",
-    "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/sentence-highlighting/opensearch-semantic-highlighter-v1",
-    "versions": {
-      "1.0.0": {
-        "format": [
-          "torch_script"
-        ],
-        "description": "A semantic highlighter model that identifies and highlights relevant sentences in a document given a query."
-      }
-    }
   }
 ]