Instructions to use javismiles/dec3v3model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use javismiles/dec3v3model 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("javismiles/dec3v3model") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-5000/optimizer.bin from javismiles/dec3v3model: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/javismiles/dec3v3model/resolve/main/checkpoint-5000/optimizer.bin
- Command line
-
hf download hf://javismiles/dec3v3model/checkpoint-5000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/javismiles/dec3v3model/resolve/main/checkpoint-5000/optimizer.bin
6.59 MB
- Xet hash:
- ec14adc9a9079b13db00131ec348b71d8932f2ceb01d8f3eadd2712b5201db6f
- Size of remote file:
- 6.59 MB
- SHA256:
- 77c413086f7ac7f3547af47496034afb54819f395b02a32a1a5b788a8adc131c
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