Update README

Author: saddam213

OnnxStack.Core/README.md

@@ -81,19 +81,19 @@ using (var tokens = _onnxModelService.RunInference(OnnxModelType.Tokenizer, inpu
 // Create Configuration
 var onnxStackConfig = new OnnxStackConfig
 {
-	Name = "OnnxStack",
-	TokenizerLimit = 77,
-	ModelConfigurations = new List<OnnxModelSessionConfig>
-	{
-		new OnnxModelSessionConfig
-		{
-				DeviceId = 0,
-				ExecutionProvider = ExecutionProvider.DirectML,
-
-				Type = OnnxModelType.Tokenizer,
-				OnnxModelPath = "clip_tokenizer.onnx",
-		}
-	}
+    Name = "OnnxStack",
+    TokenizerLimit = 77,
+    ModelConfigurations = new List<OnnxModelSessionConfig>
+    {
+        new OnnxModelSessionConfig
+        {
+            DeviceId = 0,
+            ExecutionProvider = ExecutionProvider.DirectML,
+
+            Type = OnnxModelType.Tokenizer,
+            OnnxModelPath = "clip_tokenizer.onnx",
+        }
+    }
 };
 
 // Create Service
@@ -105,14 +105,14 @@ var text = "Text To Tokenize";
 var inputTensor = new DenseTensor<string>(new string[] { text }, new int[] { 1 });
 var inputString = new List<NamedOnnxValue>
 {
-	NamedOnnxValue.CreateFromTensor("string_input", inputTensor)
+    NamedOnnxValue.CreateFromTensor("string_input", inputTensor)
 };
 
 // Create an InferenceSession from the Onnx clip tokenizer.
 // Run session and send the input data in to get inference output. 
 using (var tokens = onnxModelService.RunInference(OnnxModelType.Tokenizer, inputString))
 {
-	var resultTensor = tokens.ToArray();
+    var resultTensor = tokens.ToArray();
 }
 
 ```

OnnxStack.StableDiffusion/README.md

@@ -150,15 +150,15 @@ Each model can be assigned to its own device, which is handy if you have only a
 	},
 	"AllowedHosts": "*",
 
-	"OnnxStackConfig": {
-		"Name": "StableDiffusion 1.5",
-		"PadTokenId": 49407,
-		"BlankTokenId": 49407,
-		"InputTokenLimit": 512,
-		"TokenizerLimit": 77,
-		"EmbeddingsLength": 768,
-		"ScaleFactor": 0.18215,
-		"ModelConfigurations": [{
+   "OnnxStackConfig": {
+      "Name": "StableDiffusion 1.5",
+      "PadTokenId": 49407,
+      "BlankTokenId": 49407,
+      "InputTokenLimit": 512,
+      "TokenizerLimit": 77,
+      "EmbeddingsLength": 768,
+      "ScaleFactor": 0.18215,
+      "ModelConfigurations": [{
             "Type": "Unet",
             "DeviceId": 0,
             "ExecutionProvider": "DirectML",
@@ -195,6 +195,6 @@ Each model can be assigned to its own device, which is handy if you have only a
             "ExecutionProvider": "Cpu",
             "OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\safety_checker\\model.onnx"
          }]
-	}
+   }
 }
 ```