I need some help with uploading models to the Hugging Face repo to later access them with inference endpoints. I’m planning on training a custom DreamBooth model, but I’m confused about how to upload it. I guess I should be using PyTorchModelHubMixin, but I don’t really know how to use it in my notebook for this kind of model. Can someone please help me out?
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Hi,
Sure happy to help out. What does your model look like?
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It’s basically this: Google Colab
I managed to upload something just for testing, but I’m not really sure what to do with the above Colab notebook
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Hi @nielsr,
I would also like to know how to upload a ControlNet model to the hub and then send an image through the inference API as an input to the model
Control Net colab : Google Colab
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Hi,
As explained here, if your model is available in a native library (like Diffusers or Transformers), you can use the following:
from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained(model_path, safety_checker=None, torch_dtype=torch.float16).to("cuda")
# push to hub
pipe.push_to_hub("...")
This is explained here: Push files to the Hub.
However if you have a custom nn.Module, you can leverage the PyTorchModelHubMixin. I don’t see anything custom in your notebook which means that you can just use the native methods.
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