Text-to-Image
Diffusers
TensorBoard
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
textual_inversion
Instructions to use dxli/dog7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dxli/dog7 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_textual_inversion("dxli/dog7") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download learned_embeds-steps-3000.bin from dxli/dog7: direct link, hf CLI and curl.
- Browser
- Download file 3.94 kB
-
https://huggingface.co/dxli/dog7/resolve/main/learned_embeds-steps-3000.bin
- Command line
-
hf download hf://dxli/dog7/learned_embeds-steps-3000.bin
-
curl -L -o learned_embeds-steps-3000.bin https://huggingface.co/dxli/dog7/resolve/main/learned_embeds-steps-3000.bin
3.94 kB
- Xet hash:
- 9f42797541d2ee40742b32c148e91088c600624db51910392bfd71a561f76182
- Size of remote file:
- 3.94 kB
- SHA256:
- 614e9eab20e5204f2c9e7f18585d790eb51294f8fc6d4b7127ed3186b1805b56
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