fix links

Author: PatrickFarley

articles/ai-services/content-safety/how-to/containers/image-container.md

@@ -58,7 +58,7 @@ The following table represents the various `docker run` parameters and their cor
 | `{ENDPOINT_URI}` | The endpoint is required for metering and billing. For more information, see [billing arguments](./install-run-container.md#billing-arguments). |
 | `{API_KEY}` | The API key is required. For more information, see [billing arguments](./install-run-container.md#billing-arguments). |
 
-When you run the content safety analyze image container, configure the port, memory, and CPU according to the [requirements and recommendations](./install-run-container.md#container-requirements-and-recommendations).
+When you run the content safety analyze image container, configure the port, memory, and CPU according to the [requirements and recommendations](./install-run-container.md#host-computer-requirements-and-recommendations).
 
 Here's a sample `docker run` command with placeholder values. You must specify the `ENDPOINT_URI` and `API_KEY` values:
 
@@ -72,7 +72,7 @@ ApiKey={API_KEY}
 
 This command:
 * Runs an `image-analyze` container from the container image.
-* Uses all available GPU resources (by specifying `--gpus all`). Content safety containers require CUDA for optimal performance. Learn more in [host requirements and recommendations](./install-run-container.md#host-computer-requirements-and-recommendations). Also make sure your host installs [NVIDIA container toolkit](./install-run-container.md#installing-the-nvidia-container-toolkit).
+* Uses all available GPU resources (by specifying `--gpus all`). Content safety containers require CUDA for optimal performance. Learn more in [host requirements and recommendations](./install-run-container.md#host-computer-requirements-and-recommendations). Also make sure your host installs [NVIDIA container toolkit](./install-run-container.md#install-the-nvidia-container-toolkit).
 * Exposes TCP port 5000 and allocates a pseudo-TTY for the container.
 * Automatically removes the container after it exits. The container image is still available on the host computer.
 
@@ -150,6 +150,6 @@ Once the container is up and running, you can validate its operation by sending
 
 ## Next steps
 
-* See the [content safety containers overview](../../../container-overview.md)
+* See the [content safety containers overview](./container-overview.md)
 * Review [configure containers](./install-run-container.md) for configuration settings
 * Use more [Azure AI containers](../../../cognitive-services-container-support.md)

articles/ai-services/content-safety/how-to/containers/install-run-container.md

@@ -68,14 +68,14 @@ The table below presents the requests per second (RPS) and latency metrics obtai
 
 Even with identical GPUs, performance can fluctuate based on the GPU load and the specific configuration of the environment. The benchmark data we provide should be used as a reference point when considering the deployment of content safety containers in your environment. For the most accurate assessment, we recommend conducting tests within your specific environment.
 
-#### [Analyze text](#tqb/text)
+#### [Analyze text](#tab/text)
 
 |GPU| Max RPS| Average latency (at Max RPS)|
 |---|---|---|
 | T4 | 130 | 50.4 ms |
 | A100 | 360 | 8.7 |
 
-#### [Analyze image](#tqb/image)
+#### [Analyze image](#tab/image)
 
 |GPU| Max RPS| Average latency (at Max RPS)|
 |---|---|---|
@@ -140,7 +140,7 @@ You can have this container and a different Azure AI container running on the HO
 > [!NOTE]
 > Use a unique port number if you're running multiple containers.
 > | Protocol | Host URL |
-> |--|--
+> |--|--|
 > | WS | `ws://localhost:5000` | 
 > | HTTP | `http://localhost:5000` |
 

articles/ai-services/content-safety/how-to/containers/text-container.md

@@ -71,7 +71,7 @@ ApiKey={API_KEY}
 
 This command:
 * Runs a `content safety` container from the container image.
-* Uses all available GPU resources (by specifying `--gpus all`). Content safety container requires CUDA for optimal performance. See more in  [host requirements and recommendations](./install-run-container.md#host-computer-requirements-and-recommendations). Also make sure your host install [NVIDIA container toolkit](./install-run-container.md#installing-the-nvidia-container-toolkit)
+* Uses all available GPU resources (by specifying `--gpus all`). Content safety container requires CUDA for optimal performance. See more in  [host requirements and recommendations](./install-run-container.md#host-computer-requirements-and-recommendations). Also make sure your host install [NVIDIA container toolkit](./install-run-container.md#install-the-nvidia-container-toolkit)
 * Exposes TCP port 5000 and allocates a pseudo-TTY for the container.
 * Automatically removes the container after it exits. The container image is still available on the host computer.