How to use from the
Use from the
Diffusers library
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-stable-diffusion-torch", dtype=torch.bfloat16, device_map="cuda")
pipe.load_textual_inversion("optimum-intel-internal-testing/tiny-stable-diffusion-with-textual-inversion")

Textual inversion text2image fine-tuning - katuni4ka/textual_inversion_cat

These are textual inversion adaption weights for hf-internal-testing/tiny-stable-diffusion-torch. You can find some example images in the following.

Intended uses & limitations

How to use

# TODO: add an example code snippet for running this diffusion pipeline

Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

Training details

[TODO: describe the data used to train the model]

Downloads last month
4,090
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for optimum-intel-internal-testing/tiny-stable-diffusion-with-textual-inversion

Adapter
(2)
this model