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config.json

@@ -0,0 +1,35 @@
+{
+  "architecture": "mobilenetv3_large_100",
+  "classifier": "classifier",
+  "crop_mode": "center",
+  "crop_pct": 0.875,
+  "custom_load": false,
+  "export_model_type": "mobilenetv3_large_100",
+  "first_conv": "conv_stem",
+  "fixed_input_size": false,
+  "hf_hub_id": "timm/mobilenetv3_large_100.ra_in1k",
+  "input_size": [
+    3,
+    224,
+    224
+  ],
+  "interpolation": "bicubic",
+  "mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "num_classes": 1000,
+  "pool_size": [
+    7,
+    7
+  ],
+  "source": "hf-hub",
+  "std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "tag": "ra_in1k",
+  "transformers_version": "4.38.2"
+}

onnx/model.onnx

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+size 21949218

onnx/model_bnb4.onnx

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+size 21949237

onnx/model_fp16.onnx

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+size 11007819

onnx/model_int8.onnx

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onnx/model_q4.onnx

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+size 21949237

onnx/model_quantized.onnx

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+size 5713994

onnx/model_uint8.onnx

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quantize_config.json

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+{
+    "fp16": {},
+    "q8": {
+        "per_model_config": {
+            "model": {
+                "op_types": [
+                    "Add",
+                    "Conv",
+                    "Flatten",
+                    "Gemm",
+                    "GlobalAveragePool",
+                    "HardSigmoid",
+                    "Mul",
+                    "ReduceMean",
+                    "Relu"
+                ],
+                "weight_type": "QUInt8"
+            }
+        },
+        "per_channel": true,
+        "reduce_range": true
+    },
+    "int8": {
+        "per_model_config": {
+            "model": {
+                "op_types": [
+                    "Add",
+                    "Conv",
+                    "Flatten",
+                    "Gemm",
+                    "GlobalAveragePool",
+                    "HardSigmoid",
+                    "Mul",
+                    "ReduceMean",
+                    "Relu"
+                ],
+                "weight_type": "QInt8"
+            }
+        },
+        "per_channel": true,
+        "reduce_range": true
+    },
+    "uint8": {
+        "per_model_config": {
+            "model": {
+                "op_types": [
+                    "Add",
+                    "Conv",
+                    "Flatten",
+                    "Gemm",
+                    "GlobalAveragePool",
+                    "HardSigmoid",
+                    "Mul",
+                    "ReduceMean",
+                    "Relu"
+                ],
+                "weight_type": "QUInt8"
+            }
+        },
+        "per_channel": true,
+        "reduce_range": true
+    },
+    "q4": {
+        "block_size": 32,
+        "is_symmetric": true,
+        "accuracy_level": null
+    },
+    "bnb4": {
+        "block_size": 64,
+        "quant_type": 1
+    }
+}