Update README

Author: saddam213

OnnxStack.Core/README.md

@@ -23,7 +23,7 @@ builder.Services.AddOnnxStack();
 ```
 
 ## Configuration example
-The `appsettings.json` is the easiest option for configuring model sets. Below is an example of `Stable Diffusion 1.5`. The example adds the necessary paths to each model file required for Stable Diffusion, as well as any model-specific configurations. Each model can be assigned to its own device, which is handy if you have only a small GPU. This way, you can offload only what you need. There are limitations depending on the version of the `Microsoft.ML.OnnxRuntime` package you are using, but in most cases, you can split the load between CPU and GPU.
+The `appsettings.json` is the easiest option for configuring model sets. Below is an example of `clip tokenizer`.
 
 ```json
 {
@@ -36,50 +36,14 @@ The `appsettings.json` is the easiest option for configuring model sets. Below i
 	"AllowedHosts": "*",
 
 	"OnnxStackConfig": {
-		"Name": "StableDiffusion 1.5",
-		"PadTokenId": 49407,
-		"BlankTokenId": 49407,
-		"InputTokenLimit": 512,
+		"Name": "Clip Tokenizer",
 		"TokenizerLimit": 77,
-		"EmbeddingsLength": 768,
-		"ScaleFactor": 0.18215,
 		"ModelConfigurations": [
-			{
-				"Type": "Unet",
-				"DeviceId": 0,
-				"ExecutionProvider": "DirectML",
-				"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\unet\\model.onnx"
-			},
 			{
 				"Type": "Tokenizer",
 				"DeviceId": 0,
 				"ExecutionProvider": "Cpu",
 				"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\cliptokenizer.onnx"
-			},
-			{
-				"Type": "TextEncoder",
-				"DeviceId": 0,
-				"ExecutionProvider": "Cpu",
-				"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\text_encoder\\model.onnx"
-			},
-			{
-				"Type": "VaeEncoder",
-				"DeviceId": 0,
-				"ExecutionProvider": "Cpu",
-				"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\vae_encoder\\model.onnx"
-			},
-			{
-				"Type": "VaeDecoder",
-				"DeviceId": 0,
-				"ExecutionProvider": "Cpu",
-				"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\vae_decoder\\model.onnx"
-			},
-			{
-				"Type": "SafetyChecker",
-				"IsDisabled": true,
-				"DeviceId": 0,
-				"ExecutionProvider": "Cpu",
-				"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\safety_checker\\model.onnx"
 			}
 		]
 	}
@@ -90,6 +54,32 @@ The `appsettings.json` is the easiest option for configuring model sets. Below i
 
 ### Basic C# Example
 ```csharp
+
+// From DI
+IOnnxModelService _onnxModelService;
+
+
+// Tokenizer model Example
+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)
+};
+
+// 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();
+}
+
+```
+
+
+
+### Basic C# Example (No DI)
+```csharp
 // Create Configuration
 var onnxStackConfig = new OnnxStackConfig
 {

OnnxStack.StableDiffusion/README.md

@@ -132,4 +132,71 @@ internal class AppService : IHostedService
       return Task.CompletedTask;
    }
 }
+```
+
+
+## Configuration
+The `appsettings.json` is the easiest option for configuring model sets. Below is an example of `Stable Diffusion 1.5`.
+The example adds the necessary paths to each model file required for Stable Diffusion, as well as any model-specific configurations. 
+Each model can be assigned to its own device, which is handy if you have only a small GPU. This way, you can offload only what you need. There are limitations depending on the version of the `Microsoft.ML.OnnxRuntime` package you are using, but in most cases, you can split the load between CPU and GPU.
+
+```json
+{
+	"Logging": {
+		"LogLevel": {
+			"Default": "Information",
+			"Microsoft.AspNetCore": "Warning"
+		}
+	},
+	"AllowedHosts": "*",
+
+	"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",
+				"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\unet\\model.onnx"
+			},
+			{
+				"Type": "Tokenizer",
+				"DeviceId": 0,
+				"ExecutionProvider": "Cpu",
+				"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\cliptokenizer.onnx"
+			},
+			{
+				"Type": "TextEncoder",
+				"DeviceId": 0,
+				"ExecutionProvider": "Cpu",
+				"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\text_encoder\\model.onnx"
+			},
+			{
+				"Type": "VaeEncoder",
+				"DeviceId": 0,
+				"ExecutionProvider": "Cpu",
+				"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\vae_encoder\\model.onnx"
+			},
+			{
+				"Type": "VaeDecoder",
+				"DeviceId": 0,
+				"ExecutionProvider": "Cpu",
+				"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\vae_decoder\\model.onnx"
+			},
+			{
+				"Type": "SafetyChecker",
+				"IsDisabled": true,
+				"DeviceId": 0,
+				"ExecutionProvider": "Cpu",
+				"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\safety_checker\\model.onnx"
+			}
+		]
+	}
+}
 ```