Text-to-Image
Diffusers
TensorBoard
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
textual_inversion
Instructions to use dxli/dog3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dxli/dog3 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/dog3") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download learned_embeds.bin from dxli/dog3: direct link, hf CLI and curl.
- Browser
- Download file 3.84 kB
-
https://huggingface.co/dxli/dog3/resolve/main/learned_embeds.bin
- Command line
-
hf download hf://dxli/dog3/learned_embeds.bin
-
curl -L -o learned_embeds.bin https://huggingface.co/dxli/dog3/resolve/main/learned_embeds.bin
3.84 kB
- Xet hash:
- 66cc775ffdedfb96757e9dde89872f3d47f445a118940112992273511b8e3fe2
- Size of remote file:
- 3.84 kB
- SHA256:
- d1674b022092161c838357494c894eeedc9712c84c3c5035fd39cc4ea3778bab
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.