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.gitattributes

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+saved_model/variables/variables.data-00000-of-00001 filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+language: en
+tags:
+- tensorflow
+- image-classification
+license: mit
+datasets: []
+pipeline_tag: image-classification
+library_name: tensorflow
+---
+
+# Wrist Undertone Classifier 🩵🩷💛
+
+This TensorFlow model predicts whether a user's wrist undertone is **Cool**, **Warm**, or **Neutral** based on an uploaded image of their wrist.
+
+## 🧠 Model Details
+
+- Framework: TensorFlow (SavedModel format)
+- Input: Wrist image (`.jpg`, `.png`, etc.)
+- Output: One of three classes:  
+  - `cool`
+  - `warm`
+  - `neutral`
+
+## 🖼️ Example Usage (Python)
+
+```python
+from huggingface_hub import InferenceClient
+
+client = InferenceClient("https://huggingface.co/Salvatore7262/ronaundertone-detector")
+
+with open("my_wrist.jpg", "rb") as f:
+    result = client.post(
+        json=None,
+        data=f,
+        headers={"Content-Type": "image/jpeg"},
+    )
+
+print(result.json())

config.json

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+{
+  "architectures": ["TensorFlowImageClassificationModel"],
+  "pipeline_tag": "image-classification",
+  "library_name": "tensorflow",
+  "tags": ["image-classification", "tensorflow", "undertone", "skin-analysis"],
+  "datasets": [],
+  "language": "en",
+  "license": "mit",
+  "widget": [
+    {
+      "example_title": "Cool undertone wrist",
+      "example_url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/cat-example.jpg"
+    },
+    {
+      "example_title": "Warm undertone wrist",
+      "example_url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/dog-example.jpg"
+    }
+  ]
+}

saved_model/fingerprint.pb

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:3727459455038824342

saved_model/variables/variables.data-00000-of-00001

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