Instructions to use 12345testing/ech_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 12345testing/ech_model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("12345testing/ech_model") prompt = "a photo of object12" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- d864f12b36b2bec596dc39cb463ce067bfd194890e92d02afa1ad6bf785daabb
- Size of remote file:
- 980 kB
- SHA256:
- ff5ce6350815c92855c69b5af48cc0a357f4da537e991e40132decdeadcc3f4b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.