Instructions to use 12345testing/echo_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 12345testing/echo_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("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("12345testing/echo_model") prompt = "a photo of echo amazon" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 465bd91b0f39e94c982f23e13ac024de6b0159bff3f0aa3105583f2c0e44d0c9
- Size of remote file:
- 4.42 MB
- SHA256:
- a53ddaacf0efe474f9df67e2e09ddb46a378d50290f5ae0cf258962ae79bf54b
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