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README changes to make version references consistent
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---------

Co-authored-by: Francesco Petrini <[email protected]>
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nnshah1 and fpetrini15 authored Mar 4, 2024
1 parent 7849294 commit cb2ca25
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6 changes: 3 additions & 3 deletions Popular_Models_Guide/StableDiffusion/README.md
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Expand Up @@ -57,10 +57,10 @@ support matrix](https://docs.nvidia.com/deeplearning/frameworks/support-matrix/i
## Building the Triton Inference Server Image

The example is designed based on the
`nvcr.io/nvidia/tritonserver:YY.MM-py3` docker image and [TensorRT OSS v9.2.0](https://github.com/NVIDIA/TensorRT/releases/tag/v9.2.0).
`nvcr.io/nvidia/tritonserver:24.01-py3` docker image and [TensorRT OSS v9.2.0](https://github.com/NVIDIA/TensorRT/releases/tag/v9.2.0).

A set of convenience scripts are provided to create a docker image
based on the `nvcr.io/nvidia/tritonserver:YY.MM-py3` image with the
based on the `nvcr.io/nvidia/tritonserver:24.01-py3` image with the
dependencies for the TensorRT Stable Diffusion demo installed.

### Triton Inference Server + TensorRT OSS
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## Building and Running Stable Diffusion XL

### Start `tritonserver:rYY.MM-diffusion` Container
### Start Tritonserver Diffusion Container

The following command starts a container and volume mounts the current
directory as `workspace`.
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Expand Up @@ -55,7 +55,9 @@ output [

instance_group [
{
count: 1
kind: KIND_GPU
gpus: [0]
}
]

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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

backend: "diffusion"
max_batch_size: 2
max_batch_size: 1

dynamic_batching {
max_queue_delay_microseconds: 100000
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Expand Up @@ -50,7 +50,7 @@ git clone https://github.com/triton-inference-server/tutorials.git
cd tutorials/Triton_Inference_Server_Python_API
```

### Build `triton-python-api:rYY.MM-diffusion` Image and Stable Diffusion Models
### Build Tritonserver Image and Stable Diffusion Models

Please note the following command will take many minutes depending on
your hardware configuration and network connection.
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