Push model using huggingface_hub.

README.md

@@ -1,43 +1,14 @@
 ---
 library_name: swirl-wine-recommendations
 tags:
+- model_hub_mixin
+- pytorch_model_hub_mixin
 - recommendation
 - two-tower
 - wine
-- pytorch
 ---
 
-# Two-Tower Wine Recommendation Model
-
-Neural network for personalized wine recommendations.
-
-## Usage
-
-This model is designed to be used with HuggingFace Inference Endpoints.
-The custom `handler.py` processes requests in this format:
-
-```json
-{
-    "inputs": {
-        "user_wines": [
-            {"embedding": [768 floats], "rating": 4.5},
-            ...
-        ],
-        "candidate_wine": {
-            "embedding": [768 floats],
-            "color": "red",
-            "type": "still"
-        }
-    }
-}
-```
-
-Returns: `{"score": 75.5}`
-
-## Architecture
-
-- **User Tower**: Encodes user preferences from reviewed wines
-- **Wine Tower**: Encodes wine characteristics
-- **Output**: Match score 0-100 via dot product
-
-See [Swirl Wine App](https://swirlyourwines.com) for more info.
+This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
+- Code: [More Information Needed]
+- Paper: [More Information Needed]
+- Docs: [More Information Needed]

model.safetensors

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