model uploaded

.gitattributes

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+*.bin filter=lfs diff=lfs merge=lfs -text

README.md

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+# Garbage Classification Model
+
+A ResNet50 model fine-tuned on the Garbage Classification dataset.
+
+## Model Details
+
+- Base Architecture: ResNet50
+- Input Size: 224x224
+- Classes: battery, biological, cardboard, clothes, glass, metal, paper, plastic, shoes, trash
+
+## Usage
+
+```python
+from transformers import pipeline
+from PIL import Image
+
+# Create pipeline
+classifier = pipeline("image-classification", model="YOUR_USERNAME/garbage-classification")
+
+# Load image
+image = Image.open("test_image.jpg")
+
+# Make prediction
+result = classifier(image)
+print(f"Prediction: {result[0]['label']}, Confidence: {result[0]['score']:.2f}")
+```

config.json

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+{
+    "model_name": "resnet50",
+    "num_classes": 10,
+    "input_size": 224,
+    "classes": [
+        "battery",
+        "biological",
+        "cardboard",
+        "clothes",
+        "glass",
+        "metal",
+        "paper",
+        "plastic",
+        "shoes",
+        "trash"
+    ],
+    "normalize_mean": [
+        0.485,
+        0.456,
+        0.406
+    ],
+    "normalize_std": [
+        0.229,
+        0.224,
+        0.225
+    ],
+    "version": "1.0.0",
+    "description": "ResNet50 model fine-tuned for garbage classification"
+}

preprocessor_config.json

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+{
+    "crop_size": 224,
+    "do_center_crop": true,
+    "do_normalize": true,
+    "do_resize": true,
+    "image_mean": [0.485, 0.456, 0.406],
+    "image_std": [0.229, 0.224, 0.225],
+    "resample": 3,
+    "size": 224
+  }

pytorch_model.bin

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