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
Download checkpoint-200/optimizer.bin from 12345testing/echo_model: direct link, hf CLI and curl.
- Browser
- Download file 9.03 MB
-
https://huggingface.co/12345testing/echo_model/resolve/main/checkpoint-200/optimizer.bin
- Command line
-
hf download hf://12345testing/echo_model/checkpoint-200/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/12345testing/echo_model/resolve/main/checkpoint-200/optimizer.bin
9.03 MB
- Xet hash:
- b1afc66fd69bbbd8f7c06c80b35a792b3a6b87533a3853f974e710adfcc6bce7
- Size of remote file:
- 9.03 MB
- SHA256:
- 56ebd061cebd1cfa42099a4df0ae810997d9cbb489c6e374411b3603cf43710a
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