diff --git a/examples/usecases/llm_diffusion_serving_app/README.md b/examples/usecases/llm_diffusion_serving_app/README.md
index 48d51fdd73..98efeadeec 100644
--- a/examples/usecases/llm_diffusion_serving_app/README.md
+++ b/examples/usecases/llm_diffusion_serving_app/README.md
@@ -1,4 +1,3 @@
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## Multi-Image Generation Streamlit App: Chaining Llama & Stable Diffusion using TorchServe, torch.compile & OpenVINO
This Multi-Image Generation Streamlit app is designed to generate multiple images based on a provided text prompt. Instead of using Stable Diffusion directly, this app chains Llama and Stable Diffusion to enhance the image generation process. Here’s how it works:
@@ -7,7 +6,7 @@ This Multi-Image Generation Streamlit app is designed to generate multiple image
- For performance optimization, the models are compiled using [torch.compile using OpenVINO backend.](https://docs.openvino.ai/2024/openvino-workflow/torch-compile.html)
- The application leverages [TorchServe](https://pytorch.org/serve/) for efficient model serving and management.
-
+
## Quick Start Guide
@@ -83,12 +82,12 @@ Note: You can replace the model identifiers (MODEL_NAME_LLM, MODEL_NAME_SD) as n
## What to expect
-After launching the Docker container using the `docker run ..` command displayed after successful build, you can access two separate Streamlit applications:
+After launching the Docker container using the `docker run ..` command displayed after a successful build, you can access two separate Streamlit applications:
1. TorchServe Server App (running at http://localhost:8084) to start/stop TorchServe, load/register models, scale up/down workers.
2. Client App (running at http://localhost:8085) where you can enter prompt for Image generation.
-> Note: You could also run a quick benchmark comparing performance of Stable Diffusion with Eager, torch.compile with inductor and openvino.
-> Review the `docker run ..` command displayed after successful build for benchmarking
+> Note: You could also run a quick benchmark comparing the performance of Stable Diffusion with Eager, torch.compile with inductor and openvino.
+> Review the `docker run ..` command displayed after a successful build for benchmarking
#### Sample Output of Starting the App:
@@ -140,7 +139,7 @@ Collecting usage statistics. To deactivate, set browser.gatherUsageStats to fals
#### Sample Output of Stable Diffusion Benchmarking:
-To run Stable Diffusion benchmarking, use the `sd-benchmark.py`. See details below for sample.
+To run Stable Diffusion benchmarking, use the `sd-benchmark.py`. See details below for a sample console output.
@@ -199,7 +198,7 @@ Results saved at /home/model-server/model-store/ which is a Docker container mou
#### Sample Output of Stable Diffusion Benchmarking with Profiling:
-To run Stable Diffusion benchmarking with profiling, use `--run_profiling` or `-rp`. See details below for sample. Sample profiling benchmarking output files are available in [assets/benchmark_results_20241123_044407/](./assets/benchmark_results_20241123_044407/)
+To run Stable Diffusion benchmarking with profiling, use `--run_profiling` or `-rp`. See details below for a sample console output. Sample profiling benchmarking output files are available in [assets/benchmark_results_20241123_044407/](https://github.com/pytorch/serve/tree/master/examples/usecases/llm_diffusion_serving_app/assets/benchmark_results_20241123_044407)
@@ -264,7 +263,7 @@ Results saved at /home/model-server/model-store/ which is a Docker container mou
## Multi-Image Generation App UI
### App Workflow
-
+
### App Screenshots
@@ -272,10 +271,10 @@ Results saved at /home/model-server/model-store/ which is a Docker container mou
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| Client App Screenshot 1 | Client App Screenshot 2 | Client App Screenshot 3 |
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