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Machine Learning Toolset for Houdini
| Date | Stars |
|---|---|
| 2026-07-31 | 418 |
| 2026-08-04 | 418 |
| 2026-08-06 | 418 |
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 # Houdini MLOPs 3.0 Free and Open Source Machine Learning Plugin for Houdini developed by Ambrosiussen Holding and [Entagma](https://entagma.com/), Licensed and Distributed by [Bismuth Consultancy B.V.](https://www.bismuthconsultancy.com/) _By downloading or using the plugin (or any of its contents), you are agreeing to the LICENSE found in this repository and [Terms of Service of Bismuth Consultancy B.V.](https://www.bismuthconsultancy.com/s/EN_Terms_And_Conditions-f5sk.pdf)_ | Paul Ambrosiussen | Entagma | Discord | | --------------- | --------------- | --------------- | | [](https://twitter.com/ambrosiussen_p) | [](https://twitter.com/entagma) | [](https://discord.gg/rKr5SNZJtM) | | [](https://www.linkedin.com/in/paulambrosiussen/) | ## Promo Video <a href="http://www.youtube.com/watch?feature=player_embedded&v=izLicMTBYUg " target="_blank"><img src="http://img.youtube.com/vi/izLicMTBYUg/0.jpg" alt="2.0 Release Promo" width="640" height="480" border="0" /></a> # Installing for Houdini To install the plugin for the first time, follow these steps: 1. Clone this repository and make note of the directory you have cloned it to. 2. Copy the `MLOPs.json` file found in the repository root, and paste it in the $HOUDINI_USER_PREF_DIR/packages/ folder. 3. Edit the `MLOPs.json` file you just pasted, and modify the `$MLOPS` path found inside. Set the path to where you cloned the repository to in step one. 4. Install `git`. Follow the instructions for your relevant OS [here](https://github.com/git-guides/install-git). 5. Launch Houdini and open the `MLOPs` shelf. Click the `Install Dependencies` shelf button. Restart Houdini once complete. 6. After restarting Houdini, open the `MLOPs` shelf. Click the `Download Model` button. Optionally change the `Model Name` parameter to a custom model, or just leave as is and hit `Download` to work with the default Stable Diffusion Model. 7. In the MLOPs nodes, use the dropdown on the `[type] Model` parameters to select a downloaded model to use. You can also provide a repo name from the [Huggingface Library](https://huggingface.co/models?pipeline_tag=text-to-image&sort=downloads), and the nodes will download it for you. For example `runwayml/stable-diffusion-v1-5`. # Downloading Models - By default, `$MLOPS_SD_MODEL` is the path to a SINGLE model used by all Stable Diffusion nodes by default. You can set this to be your preferred default model. - By default, the plugin will cache all downloaded models to the folder specified by `$MLOPS_MODELS`. (Notice the S at the end) This will make them show up in the dropdowns for the model paths on the nodes. Both of the above varibles can be changed in the `MLOPS.json` to suit your preference. # Troubleshooting - If you get an error saying "Torch not compiled with CUDA enabled". Uninstall pytorch in your system python, restart your PC and hit the `Install Dependencies` shelf button again. - Metal users should set the compute device on MLOPs nodes to "MPS", and set the following environment variable for it to work: `PYTORCH_ENABLE_MPS_FALLBACK=1` - If you get an error with "Could not load library cudnn_cnn_infer64_8.dll" and you have Octane installed as a plugin for Houdini, try disabling it and restart Houdini. - If you get an error similar to: "Unexpected self.size(-1) must be divisible by 4 to view Byte as Float (different element sizes), but got 2683502, <class 'RuntimeError'>". Try deleting the model cache in `$MLOPS_MODELS/cache/[your model]` and try again. This is
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