Instructions to use IsaacAkintaro/household_diffusion_tutorial_output_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use IsaacAkintaro/household_diffusion_tutorial_output_v2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("IsaacAkintaro/household_diffusion_tutorial_output_v2", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Commit History
-
Epoch 49
Verified signaturef55cf07 -
Epoch 44
Verified signature00bedae -
Epoch 39
Verified signatured93d5bc -
Epoch 34
Verified signature3d84173 -
Epoch 29
Verified signature02ffd15 -
Epoch 24
Verified signaturec88a96c -
Epoch 19
Verified signature87dafdb -
Epoch 14
Verified signature5903e8f -
Epoch 9
Verified signature74914d3 -
Epoch 4
Verified signature7fd6d5a -
Epoch 49
Verified signaturee97e08d -
Epoch 44
Verified signature1e15aea -
Epoch 39
Verified signature5368692 -
Epoch 34
Verified signature5abcbf8 -
Epoch 29
Verified signaturec987d92 -
Epoch 24
Verified signature37a5dd2 -
Epoch 19
Verified signaturea126330 -
Epoch 14
Verified signature3bc96c0 -
Epoch 9
Verified signature6f4c1fa -
Epoch 4
Verified signature022543a