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-2000.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-2000.bin
- Command line
-
hf download hf://dxli/dog7/learned_embeds-steps-2000.bin
-
curl -L -o learned_embeds-steps-2000.bin https://huggingface.co/dxli/dog7/resolve/main/learned_embeds-steps-2000.bin
3.94 kB
- Xet hash:
- c04a7833157979caade0d574f78ee2bbbce7a7f11626a61ac215b2010df2d765
- Size of remote file:
- 3.94 kB
- SHA256:
- 673010d158ead8c95c46f08975b34826b0384c43660e529dc99361a875ea5215
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.