Instructions to use MirageML/lowpoly-japan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MirageML/lowpoly-japan with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MirageML/lowpoly-japan", dtype=torch.bfloat16, device_map="cuda") 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
Commit History
-
Add `scale_factor` to vae config. (#2)
- Add `scale_factor` to vae config. (dfada2b4cb53cdd6ef2499084389794cf6257680) Co-authored-by: Suraj Patil <valhalla@users.noreply.huggingface.co>65be623
-
Create README.md
9e98171 -
Upload vae/diffusion_pytorch_model.bin with huggingface_hub
a4eee7d -
Upload vae/config.json with huggingface_hub
712ca21 -
Upload unet/diffusion_pytorch_model.bin with huggingface_hub
fd84770 -
Upload unet/config.json with huggingface_hub
9addbf9 -
Upload tokenizer/vocab.json with huggingface_hub
b354e08 -
Upload tokenizer/tokenizer_config.json with huggingface_hub
88fa861 -
Upload tokenizer/special_tokens_map.json with huggingface_hub
28219d4 -
Upload tokenizer/merges.txt with huggingface_hub
5b45b8f -
Upload text_encoder/pytorch_model.bin with huggingface_hub
688e9ae -
Upload text_encoder/config.json with huggingface_hub
1c4322f -
Upload scheduler/scheduler_config.json with huggingface_hub
21acb2e -
Upload model_index.json with huggingface_hub
1454300 -
Upload logs/dreambooth/events.out.tfevents.1669934780.ip-172-31-7-222.ec2.internal.50.0 with huggingface_hub
908c02a -
Upload logs/dreambooth/1669934780.4886925/hparams.yml with huggingface_hub
b082fc8 -
Upload logs/dreambooth/1669934780.4876134/events.out.tfevents.1669934780.ip-172-31-7-222.ec2.internal.50.1 with huggingface_hub
06a1590 -
initial commit
b7910f4