Skip to content

Add Wan2.2 example #3029

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
peterschmidt85 merged 3 commits into from
Aug 27, 2025
Merged

Add Wan2.2 example #3029

Show file tree
Hide file tree
Changes from 1 commit
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
dbb2d55
Add Wan2.2 example
r4victor Aug 26, 2025
8bebb07
Replaced the dev environment with a task; improved configuration (uv,…
peterschmidt85 Aug 27, 2025
a6d11d1
Forgotten change
peterschmidt85 Aug 27, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
41 changes: 41 additions & 0 deletions examples/models/wan22/README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,41 @@
# Wan2.2

[Wan2.2](https://github.com/Wan-Video/Wan2.2) is an open-source SOTA foundational video model. This example shows how to run the T2V-A14B model variant via `dstack` for text-to-video generation.

??? info "Prerequisites"
Once `dstack` is [installed](https://dstack.ai/docs/installation), clone the repo with examples.

<div class="termy">

```shell
$ git clone https://github.com/dstackai/dstack
$ cd dstack
```

</div>

Apply the [configuration](https://github.com/dstackai/dstack/blob/master/examples/models/wan22/dev-env.dstack.yml) to provision a GPU instance and run a dev environment with all the Wan2.2 dependencies installed:

<div class="termy">

```shell
$ dstack apply -f examples/models/wan22/dev-env.dstack.yml
Provisioning...
---> 100%
```

</div>

Then you can attach to the dev environment and generate videos:

<div class="termy">

```shell
Copy link
Copy Markdown
Contributor

@peterschmidt85 peterschmidt85 Aug 26, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Also, I guess its better to pass $DSTACK_GPUS_NUM instead of hardcoding 8

Copy link
Copy Markdown
Contributor

@peterschmidt85 peterschmidt85 Aug 26, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Plus we could check the number of GPUs and run single GPU version if its 1.

Copy link
Copy Markdown
Collaborator Author

@r4victor r4victor Aug 27, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

You mean replacing direct torchrun call with an if statement?

Copy link
Copy Markdown
Contributor

@peterschmidt85 peterschmidt85 Aug 27, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Perhaps we could run it as a task, and yes, have an if?

$ torchrun --nproc_per_node=8 generate.py --task t2v-A14B --size 1280*720 --ckpt_dir ./Wan2.2-T2V-A14B --dit_fsdp --t5_fsdp --ulysses_size 8 --prompt "Two anthropomorphic cats in comfy boxing gear and bright gloves fight intensely on a spotlighted stage."
Copy link
Copy Markdown
Contributor

@peterschmidt85 peterschmidt85 Aug 26, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

I assume, you first need to invoke

uv pip install --upgrade pip setuptools wheel
uv pip install flash-attn --no-build-isolation
uv pip install .

Copy link
Copy Markdown
Collaborator Author

@r4victor r4victor Aug 27, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

All required deps are installed in init

Copy link
Copy Markdown
Contributor

@peterschmidt85 peterschmidt85 Aug 27, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Hmm, strange, you are right, but it didn't work out of the box. Will try one more time

Copy link
Copy Markdown
Contributor

@peterschmidt85 peterschmidt85 Aug 27, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Here we go
Screenshot 2025-08-27 at 08 45 31

Copy link
Copy Markdown
Contributor

@peterschmidt85 peterschmidt85 Aug 27, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Also from the dstack apply log:

wan22 provisioning completed (running)
/tmp/vscode-server- 100%[===================>]  66.04M   233MB/s    in 0.3s
mkdir: created directory '/root/.vscode-server'
mkdir: created directory '/root/.vscode-server/bin'
mkdir: created directory '/root/.vscode-server/bin/6f17636121051a53c88d3e605c491d22af2ba755'
Installing extensions...
Installing extension 'ms-python.python'...
Installing extension 'ms-toolsai.jupyter'...
Extension 'ms-toolsai.jupyter-keymap' v1.1.2 was successfully installed.
Extension 'ms-toolsai.vscode-jupyter-cell-tags' v0.1.9 was successfully installed.
Extension 'ms-toolsai.vscode-jupyter-slideshow' v0.1.6 was successfully installed.
Extension 'ms-python.vscode-python-envs' v1.2.0 was successfully installed.
Extension 'ms-toolsai.jupyter-renderers' v1.3.0 was successfully installed.
Extension 'ms-toolsai.jupyter' v2025.7.0 was successfully installed.
Extension 'ms-python.debugpy' v2025.10.0 was successfully installed.
Extension 'ms-python.python' v2025.12.0 was successfully installed.
Extension 'ms-python.vscode-pylance' v2025.7.1 was successfully installed.
pip install ipykernel...

Collecting torch
  Downloading torch-2.8.0-cp313-cp313-manylinux_2_28_x86_64.whl.metadata (30 kB)
Collecting filelock (from torch)
  Downloading filelock-3.19.1-py3-none-any.whl.metadata (2.1 kB)
Collecting typing-extensions>=4.10.0 (from torch)                                                                                                                                                         Downloading typing_extensions-4.15.0-py3-none-any.whl.metadata (3.3 kB)
Collecting setuptools (from torch)
  Downloading setuptools-80.9.0-py3-none-any.whl.metadata (6.6 kB)
Collecting sympy>=1.13.3 (from torch)                                                                                                                                                                     Downloading sympy-1.14.0-py3-none-any.whl.metadata (12 kB)
Collecting networkx (from torch)
  Downloading networkx-3.5-py3-none-any.whl.metadata (6.3 kB)
Collecting jinja2 (from torch)                                                                                                                                                                            Downloading jinja2-3.1.6-py3-none-any.whl.metadata (2.9 kB)
Collecting fsspec (from torch)
  Downloading fsspec-2025.7.0-py3-none-any.whl.metadata (12 kB)
Collecting nvidia-cuda-nvrtc-cu12==12.8.93 (from torch)                                                                                                                                                   Downloading nvidia_cuda_nvrtc_cu12-12.8.93-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl.metadata (1.7 kB)
Collecting nvidia-cuda-runtime-cu12==12.8.90 (from torch)
  Downloading nvidia_cuda_runtime_cu12-12.8.90-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (1.7 kB)
Collecting nvidia-cuda-cupti-cu12==12.8.90 (from torch)                                                                                                                                                   Downloading nvidia_cuda_cupti_cu12-12.8.90-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (1.7 kB)
Collecting nvidia-cudnn-cu12==9.10.2.21 (from torch)
  Downloading nvidia_cudnn_cu12-9.10.2.21-py3-none-manylinux_2_27_x86_64.whl.metadata (1.8 kB)
Collecting nvidia-cublas-cu12==12.8.4.1 (from torch)                                                                                                                                                      Downloading nvidia_cublas_cu12-12.8.4.1-py3-none-manylinux_2_27_x86_64.whl.metadata (1.7 kB)
Collecting nvidia-cufft-cu12==11.3.3.83 (from torch)
  Downloading nvidia_cufft_cu12-11.3.3.83-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (1.7 kB)
Collecting nvidia-curand-cu12==10.3.9.90 (from torch)                                                                                                                                                     Downloading nvidia_curand_cu12-10.3.9.90-py3-none-manylinux_2_27_x86_64.whl.metadata (1.7 kB)
Collecting nvidia-cusolver-cu12==11.7.3.90 (from torch)
  Downloading nvidia_cusolver_cu12-11.7.3.90-py3-none-manylinux_2_27_x86_64.whl.metadata (1.8 kB)
Collecting nvidia-cusparse-cu12==12.5.8.93 (from torch)                                                                                                                                                   Downloading nvidia_cusparse_cu12-12.5.8.93-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (1.8 kB)
Collecting nvidia-cusparselt-cu12==0.7.1 (from torch)
  Downloading nvidia_cusparselt_cu12-0.7.1-py3-none-manylinux2014_x86_64.whl.metadata (7.0 kB)
Collecting nvidia-nccl-cu12==2.27.3 (from torch)                                                                                                                                                          Downloading nvidia_nccl_cu12-2.27.3-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (2.0 kB)
Collecting nvidia-nvtx-cu12==12.8.90 (from torch)
  Downloading nvidia_nvtx_cu12-12.8.90-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (1.8 kB)
Collecting nvidia-nvjitlink-cu12==12.8.93 (from torch)
  Downloading nvidia_nvjitlink_cu12-12.8.93-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl.metadata (1.7 kB)
Collecting nvidia-cufile-cu12==1.13.1.3 (from torch)
  Downloading nvidia_cufile_cu12-1.13.1.3-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (1.7 kB)
Collecting triton==3.4.0 (from torch)
  Downloading triton-3.4.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.metadata (1.7 kB)
Collecting mpmath<1.4,>=1.1.0 (from sympy>=1.13.3->torch)
  Downloading mpmath-1.3.0-py3-none-any.whl.metadata (8.6 kB)
Collecting MarkupSafe>=2.0 (from jinja2->torch)
  Downloading MarkupSafe-3.0.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (4.0 kB)
Downloading torch-2.8.0-cp313-cp313-manylinux_2_28_x86_64.whl (887.9 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 887.9/887.9 MB 94.7 MB/s  0:00:06
Downloading nvidia_cublas_cu12-12.8.4.1-py3-none-manylinux_2_27_x86_64.whl (594.3 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 594.3/594.3 MB 183.9 MB/s  0:00:03
Downloading nvidia_cuda_cupti_cu12-12.8.90-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (10.2 MB)                                                                                               ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 10.2/10.2 MB 190.4 MB/s  0:00:00
Downloading nvidia_cuda_nvrtc_cu12-12.8.93-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl (88.0 MB)                                                                                               ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 88.0/88.0 MB 315.0 MB/s  0:00:00
Downloading nvidia_cuda_runtime_cu12-12.8.90-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (954 kB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 954.8/954.8 kB 73.4 MB/s  0:00:00
Downloading nvidia_cudnn_cu12-9.10.2.21-py3-none-manylinux_2_27_x86_64.whl (706.8 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 706.8/706.8 MB 158.4 MB/s  0:00:03
Downloading nvidia_cufft_cu12-11.3.3.83-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (193.1 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 193.1/193.1 MB 271.9 MB/s  0:00:00                                                                                                                          Downloading nvidia_cufile_cu12-1.13.1.3-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (1.2 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.2/1.2 MB 61.1 MB/s  0:00:00
Downloading nvidia_curand_cu12-10.3.9.90-py3-none-manylinux_2_27_x86_64.whl (63.6 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 63.6/63.6 MB 245.7 MB/s  0:00:00                                                                                                                            Downloading nvidia_cusolver_cu12-11.7.3.90-py3-none-manylinux_2_27_x86_64.whl (267.5 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 267.5/267.5 MB 358.1 MB/s  0:00:00
Downloading nvidia_cusparse_cu12-12.5.8.93-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (288.2 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 288.2/288.2 MB 298.6 MB/s  0:00:00
Downloading nvidia_cusparselt_cu12-0.7.1-py3-none-manylinux2014_x86_64.whl (287.2 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 287.2/287.2 MB 319.0 MB/s  0:00:00                                                                                                                          Downloading nvidia_nccl_cu12-2.27.3-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (322.4 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 322.4/322.4 MB 306.8 MB/s  0:00:01                                                                                                                          Downloading nvidia_nvjitlink_cu12-12.8.93-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl (39.3 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 39.3/39.3 MB 254.3 MB/s  0:00:00                                                                                                                            Downloading nvidia_nvtx_cu12-12.8.90-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (89 kB)
Downloading triton-3.4.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (155.6 MB)                                                                                                            ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 155.6/155.6 MB 119.5 MB/s  0:00:01
Downloading setuptools-80.9.0-py3-none-any.whl (1.2 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.2/1.2 MB 79.2 MB/s  0:00:00
Downloading sympy-1.14.0-py3-none-any.whl (6.3 MB)                                                                                                                                                         ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 6.3/6.3 MB 188.1 MB/s  0:00:00
Downloading mpmath-1.3.0-py3-none-any.whl (536 kB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 536.2/536.2 kB 38.5 MB/s  0:00:00
Downloading typing_extensions-4.15.0-py3-none-any.whl (44 kB)                                                                                                                                           Downloading filelock-3.19.1-py3-none-any.whl (15 kB)
Downloading fsspec-2025.7.0-py3-none-any.whl (199 kB)
Downloading jinja2-3.1.6-py3-none-any.whl (134 kB)
Downloading MarkupSafe-3.0.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (23 kB)                                                                                                         Downloading networkx-3.5-py3-none-any.whl (2.0 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2.0/2.0 MB 106.3 MB/s  0:00:00
Installing collected packages: nvidia-cusparselt-cu12, mpmath, typing-extensions, sympy, setuptools, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufile-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, networkx, MarkupSafe, fsspec, filelock, triton, nvidia-cusparse-cu12, nvidia-cufft-cu12, nvidia-cudnn-cu12, jinja2, nvidia-cusolver-cu12, torch
Successfully installed MarkupSafe-3.0.2 filelock-3.19.1 fsspec-2025.7.0 jinja2-3.1.6 mpmath-1.3.0 networkx-3.5 nvidia-cublas-cu12-12.8.4.1 nvidia-cuda-cupti-cu12-12.8.90 nvidia-cuda-nvrtc-cu12-12.8.93 nvidia-cuda-runtime-cu12-12.8.90 nvidia-cudnn-cu12-9.10.2.21 nvidia-cufft-cu12-11.3.3.83 nvidia-cufile-cu12-1.13.1.3 nvidia-curand-cu12-10.3.9.90 nvidia-cusolver-cu12-11.7.3.90 nvidia-cusparse-cu12-12.5.8.93 nvidia-cusparselt-cu12-0.7.1 nvidia-nccl-cu12-2.27.3 nvidia-nvjitlink-cu12-12.8.93 nvidia-nvtx-cu12-12.8.90 setuptools-80.9.0 sympy-1.14.0 torch-2.8.0 triton-3.4.0 typing-extensions-4.15.0
Requirement already satisfied: torch>=2.4.0 in ./.venv/lib/python3.13/site-packages (from -r requirements.txt (line 1)) (2.8.0)
Collecting torchvision>=0.19.0 (from -r requirements.txt (line 2))
  Downloading torchvision-0.23.0-cp313-cp313-manylinux_2_28_x86_64.whl.metadata (6.1 kB)
Collecting opencv-python>=4.9.0.80 (from -r requirements.txt (line 3))
  Downloading opencv_python-4.12.0.88-cp37-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (19 kB)
Collecting diffusers>=0.31.0 (from -r requirements.txt (line 4))
  Downloading diffusers-0.35.1-py3-none-any.whl.metadata (20 kB)
Collecting transformers>=4.49.0 (from -r requirements.txt (line 5))
  Downloading transformers-4.55.4-py3-none-any.whl.metadata (41 kB)
Collecting tokenizers>=0.20.3 (from -r requirements.txt (line 6))
  Downloading tokenizers-0.21.4-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (6.7 kB)
Collecting accelerate>=1.1.1 (from -r requirements.txt (line 7))
  Downloading accelerate-1.10.1-py3-none-any.whl.metadata (19 kB)
Collecting tqdm (from -r requirements.txt (line 8))
  Downloading tqdm-4.67.1-py3-none-any.whl.metadata (57 kB)
Collecting easydict (from -r requirements.txt (line 10))
  Downloading easydict-1.13-py3-none-any.whl.metadata (4.2 kB)
Collecting ftfy (from -r requirements.txt (line 11))
  Downloading ftfy-6.3.1-py3-none-any.whl.metadata (7.3 kB)
Collecting dashscope (from -r requirements.txt (line 12))
  Downloading dashscope-1.24.2-py3-none-any.whl.metadata (7.1 kB)
Collecting imageio-ffmpeg (from -r requirements.txt (line 13))
  Downloading imageio_ffmpeg-0.6.0-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)
Collecting flash_attn (from -r requirements.txt (line 14))
  Downloading flash_attn-2.8.3.tar.gz (8.4 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 8.4/8.4 MB 63.7 MB/s  0:00:00
  Installing build dependencies ... done
  Getting requirements to build wheel ... error
  error: subprocess-exited-with-error

  × Getting requirements to build wheel did not run successfully.
  │ exit code: 1
  ╰─> [23 lines of output]
      Traceback (most recent call last):
        File "/workflow/.venv/lib/python3.13/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 389, in <module>
          main()
          ~~~~^^
        File "/workflow/.venv/lib/python3.13/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 373, in main
          json_out["return_val"] = hook(**hook_input["kwargs"])
                                   ~~~~^^^^^^^^^^^^^^^^^^^^^^^^
        File "/workflow/.venv/lib/python3.13/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 143, in get_requires_for_build_wheel
          return hook(config_settings)
        File "/tmp/pip-build-env-v4zruigi/overlay/lib/python3.13/site-packages/setuptools/build_meta.py", line 331, in get_requires_for_build_wheel
          return self._get_build_requires(config_settings, requirements=[])
                 ~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
        File "/tmp/pip-build-env-v4zruigi/overlay/lib/python3.13/site-packages/setuptools/build_meta.py", line 301, in _get_build_requires
          self.run_setup()
          ~~~~~~~~~~~~~~^^
        File "/tmp/pip-build-env-v4zruigi/overlay/lib/python3.13/site-packages/setuptools/build_meta.py", line 512, in run_setup
          super().run_setup(setup_script=setup_script)
          ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^
        File "/tmp/pip-build-env-v4zruigi/overlay/lib/python3.13/site-packages/setuptools/build_meta.py", line 317, in run_setup
          exec(code, locals())
          ~~~~^^^^^^^^^^^^^^^^
        File "<string>", line 22, in <module>
      ModuleNotFoundError: No module named 'torch'
      [end of output]

  note: This error originates from a subprocess, and is likely not a problem with pip.
error: subprocess-exited-with-error

× Getting requirements to build wheel did not run successfully.
│ exit code: 1
╰─> See above for output.

note: This error originates from a subprocess, and is likely not a problem with pip.
Collecting huggingface_hub[cli]
  Downloading huggingface_hub-0.34.4-py3-none-any.whl.metadata (14 kB)
...

Copy link
Copy Markdown
Contributor

@peterschmidt85 peterschmidt85 Aug 27, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

But even if I install all correctly:

I still, it still requires decord and librosa - otherwise, it fails.

For some reason, these libraries are not included into the project deps but required.


[2025-08-26 05:41:54,911] INFO: Input prompt: Two anthropomorphic cats in comfy boxing gear and bright gloves fight intensely on a spotlighted stage.
[2025-08-26 05:41:54,912] INFO: Creating WanT2V pipeline.
[2025-08-26 05:42:50,296] INFO: loading ./Wan2.2-T2V-A14B/models_t5_umt5-xxl-enc-bf16.pth
```

</div>
17 changes: 17 additions & 0 deletions examples/models/wan22/dev-env.dstack.yml
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,17 @@
type: dev-environment
name: wan22
ide: vscode
nvcc: true
repos:
- https://github.com/Wan-Video/Wan2.2.git
init:
- |
pip install torch
pip install -r requirements.txt
pip install "huggingface_hub[cli]"
huggingface-cli download Wan-AI/Wan2.2-T2V-A14B --local-dir ./Wan2.2-T2V-A14B
resources:
gpu:
name: H100
count: 8 # Set to 1.. if 8 GPUs not available trading inferece speed
disk: 200GB
Loading