Instructions to use July66/julijxtm2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use July66/julijxtm2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("July66/julijxtm2", 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
-
Upload folder using huggingface_hub
b28bfd4 -
Upload model_index.json with huggingface_hub
16ef4aa -
Upload folder using huggingface_hub
955cc52 -
Upload folder using huggingface_hub
f030e34 -
Upload folder using huggingface_hub
6dcdb72 -
Upload folder using huggingface_hub
f57832e -
Upload folder using huggingface_hub
ecdc9f5 -
Upload folder using huggingface_hub
b7885f0 -
Upload the concept julijxtm2 embeds and token
cf0a1c5 -
initial commit
c4c39fa