feat: Added ClipVitB32 model to support text-to-image search. (Anush0…

…08#126)

README.md

@@ -28,6 +28,7 @@ The default model is Flag Embedding, which is top of the [MTEB](https://huggingf
 - [**BAAI/bge-small-en-v1.5**](https://huggingface.co/BAAI/bge-small-en-v1.5) - Default
 - [**sentence-transformers/all-MiniLM-L6-v2**](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2)
 - [**mixedbread-ai/mxbai-embed-large-v1**](https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1)
+- [**Qdrant/clip-ViT-B-32-text**](https://huggingface.co/Qdrant/clip-ViT-B-32-text) - pairs with the image model clip-ViT-B-32-vision for image-to-text search
 
 <details>
   <summary>Click to see full List</summary>

src/models/text_embedding.rs

@@ -63,6 +63,8 @@ pub enum EmbeddingModel {
     GTELargeENV15,
     /// Quantized Alibaba-NLP/gte-large-en-v1.5
     GTELargeENV15Q,
+    /// Qdrant/clip-ViT-B-32-text
+    ClipVitB32,
 }
 
 /// Centralized function to initialize the models map.
@@ -256,6 +258,13 @@ fn init_models_map() -> HashMap<EmbeddingModel, ModelInfo<EmbeddingModel>> {
             model_code: String::from("Alibaba-NLP/gte-large-en-v1.5"),
             model_file: String::from("onnx/model_quantized.onnx"),
         },
+        ModelInfo {
+            model: EmbeddingModel::ClipVitB32,
+            dim: 512,
+            description: String::from("CLIP text encoder based on ViT-B/32"),
+            model_code: String::from("Qdrant/clip-ViT-B-32-text"),
+            model_file: String::from("model.onnx"),
+        },
     ];
 
     // TODO: Use when out in stable
@@ -327,6 +336,8 @@ impl EmbeddingModel {
             EmbeddingModel::GTEBaseENV15Q => Some(Pooling::Cls),
             EmbeddingModel::GTELargeENV15 => Some(Pooling::Cls),
             EmbeddingModel::GTELargeENV15Q => Some(Pooling::Cls),
+
+            EmbeddingModel::ClipVitB32 => Some(Pooling::Mean),
         }
     }
 

tests/embeddings.rs

@@ -61,6 +61,7 @@ fn verify_embeddings(model: &EmbeddingModel, embeddings: &[Embedding]) -> Result
         EmbeddingModel::ParaphraseMLMiniLML12V2 => [-0.07795018, -0.059113946, -0.043668486, -0.1880083],
         EmbeddingModel::ParaphraseMLMiniLML12V2Q => [-0.07749095, -0.058981877, -0.043487836, -0.18775631],
         EmbeddingModel::ParaphraseMLMpnetBaseV2 => [0.39132136, 0.49490625, 0.65497226, 0.34237382],
+        EmbeddingModel::ClipVitB32 => [0.7057363, 1.3549932, 0.46823958, 0.52351093],
         _ => panic!("Model {model} not found. If you have just inserted this `EmbeddingModel` variant, please update the expected embeddings."),
     };