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Add Wan2.1 to PyTorch inference Docker documentation (#4984)

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* add wan2.1 to pyt inference models

* update group name

* fix container tag

* fix group name

* change documented data type to bfloat16

* fix col width
This commit is contained in:
Peter Park
2025-07-02 09:58:37 -04:00
committed by GitHub
parent 73de8a3e46
commit d0c8ba0805
2 changed files with 11 additions and 3 deletions
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8
docs/data/how-to/rocm-for-ai/inference/pytorch-inference-benchmark-models.yaml
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@@ -31,3 +31,11 @@ pytorch_inference_benchmark:
model_repo: genmo/mochi-1-preview
url: https://huggingface.co/genmo/mochi-1-preview
precision: float16
- group: Wan2.1
tag: wan
models:
- model: Wan2.1
mad_tag: pyt_wan2.1_inference
model_repo: Wan-AI/Wan2.1-T2V-14B
url: https://huggingface.co/Wan-AI/Wan2.1-T2V-14B
precision: bfloat16

6
docs/how-to/rocm-for-ai/inference/benchmark-docker/pytorch-inference.rst
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@@ -32,10 +32,10 @@ PyTorch inference performance testing
<div id="vllm-benchmark-ud-params-picker" class="container-fluid">
<div class="row">
<div class="col-2 me-2 model-param-head">Model group</div>
<div class="col-2 me-2 model-param-head">Model</div>
<div class="row col-10">
{% for model_group in model_groups %}
<div class="col-4 model-param" data-param-k="model-group" data-param-v="{{ model_group.tag }}" tabindex="0">{{ model_group.group }}</div>
<div class="col-3 model-param" data-param-k="model-group" data-param-v="{{ model_group.tag }}" tabindex="0">{{ model_group.group }}</div>
{% endfor %}
</div>
</div>
@@ -103,7 +103,7 @@ PyTorch inference performance testing
The Chai-1 benchmark uses a specifically selected Docker image using ROCm 6.2.3 and PyTorch 2.3.0 to address an accuracy issue.
.. container:: model-doc pyt_clip_inference pyt_mochi_video_inference
.. container:: model-doc pyt_clip_inference pyt_mochi_video_inference pyt_wan2.1_inference
Use the following command to pull the `ROCm PyTorch Docker image <https://hub.docker.com/layers/rocm/pytorch/latest/images/sha256-05b55983e5154f46e7441897d0908d79877370adca4d1fff4899d9539d6c4969>`_ from Docker Hub.