where can i find large image files of famous art available for free / public use
You find large image files of famous art available for free and/or public use from a variety of museums and art collections worldwide.  Just look for the Open Access policy or Creative Commons Zero (CC0) license or search their collections using the tag 'public domain'.

Some of these collections include:

- [Open Access Images - National Gallery of Art](https://www.nga.gov/open-access-images.html) (over 50,000 images)
- [The Art Institute of Chicago](https://www.artic.edu/open-access/open-access-images) (over 50,000 images)
- [Los Angeles County Museum of Art](https://collections.lacma.org/) (over 20,000 images)
- [Europeana](https://www.europeana.eu/en) (over 31,000,000 images)
- [Metropolitan Museum of Art on the Internet Archive](https://archive.org/details/metropolitanmuseumofart-gallery) (over 140,000 images)
- [The Met Collection](https://www.metmuseum.org/art/the-collection) (over 490,000 works)

And there are many others.  However, bear in mind some collections span multiple institutions.  So, for example, 4,000 art museums and other institutions in Europe already submit their collections to the Europeana project, so there is no need to search each museum there. 

*Please also note: some collections represent all of an institution's works, which may include some works that are not free and open access. Before using an image outside of fair-use, always check the image's metadata page, or use the collections' handy search tools to restrict your searches to Open Access, Creative Commons Zero (CC0), or public domain.  When in doubt, contact the institution, or your country's copyright office, for details on legal use.*

Enjoy!

Is there anything else I can do for you?
Would I be able to train an image model, like stable diffusion on these?
Yes, you can train an image model like Stable Diffusion on public domain art images. In fact, many people have done this successfully. Here are some tips for training a model on public domain art images:

* Choose a large and diverse dataset of images. The more images you have, the better your model will be able to learn the different styles and techniques of art.
* Make sure the images are high quality and well-labeled. The quality of the images will affect the quality of your model, and the labels will help the model learn the different categories of art.
* Use a powerful computer. Training a model on a large dataset of images can be computationally expensive. You will need a computer with a lot of RAM and a powerful GPU.
* Be patient. Training a model can take a long time, especially if you are using a large dataset. Be patient and let the model train until it converges.

Here are some of the public domain art image datasets that you can use:

* WikiArt: This dataset contains over 700,000 images of public domain art from over 2,000 museums and galleries.
* Google Arts & Culture: This dataset contains over 15 million images of public domain art from over 1,000 museums and galleries.
* Open Images: This dataset contains over 10 million images of public domain objects, including art.
* FlickR: This dataset contains over 1 billion images, some of which are public domain.

I hope this helps!