Qwen3-embedding notebook (#3050)

TODO: add implementation with OV GenAI

Author: openvino-dev-samples

.ci/spellcheck/.pyspelling.wordlist.txt

@@ -81,6 +81,7 @@ bicubic
 bilinear
 biometrics
 BiT
+bitext
 blockwise
 BLACKBOX
 boolean
@@ -602,6 +603,7 @@ MosaicPretrainedTransformer
 mpnet
 mpt
 MPT
+MRL
 MRPC
 mRoPE
 msi
@@ -863,6 +865,7 @@ repo
 reproducibility
 rerank
 Rerank
+reranking
 reranker
 resampler
 Resampler

notebooks/qwen3-embedding/README.md

@@ -0,0 +1,23 @@
+# Text Embedding and Reranker with Qwen3 and OpenVINO
+
+The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. Building upon the dense foundational models of the Qwen3 series, it provides a comprehensive range of text embeddings and reranking models in various sizes (0.6B, 4B, and 8B). This series inherits the exceptional multilingual capabilities, long-text understanding, and reasoning skills of its foundational model. The Qwen3 Embedding series represents significant advancements in multiple text embedding and ranking tasks, including text retrieval, code retrieval, text classification, text clustering, and bitext mining.
+
+<img src="https://qianwen-res.oss-accelerate.aliyuncs.com/logo_qwen_embedding.png" width="400"/>
+
+In this tutorial we consider how to convert and optimize Qwen3 Embedding and Reranker model using OpenVINO.
+
+### Notebook Contents
+
+The tutorial consists of the following steps:
+
+- Prerequisites
+- Select model
+- Convert model using Optimum Intel
+- Run OpenVINO model inference with Optimum-intel
+
+## Installation Instructions
+
+This is a self-contained example that relies solely on its own code.</br>
+We recommend running the notebook in a virtual environment. You only need a Jupyter server to start.
+For further details, please refer to [Installation Guide](../../README.md).
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=5b5a4db0-7875-4bfb-bdbd-01698b5b1a77&file=notebooks/qwen3-embedding/README.md" />