Instructions to use anshumansinghr/OmegaMoonWatch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use anshumansinghr/OmegaMoonWatch with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("LAXMAYDAY/FLUX.2-dev-int8-tensorwise", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("anshumansinghr/OmegaMoonWatch") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from anshumansinghr/OmegaMoonWatch: direct link, hf CLI and curl.
- Browser
- Download file 496 Bytes
-
https://huggingface.co/anshumansinghr/OmegaMoonWatch/resolve/main/README.md
- Command line
-
hf download hf://anshumansinghr/OmegaMoonWatch/README.md
-
curl -L -o README.md https://huggingface.co/anshumansinghr/OmegaMoonWatch/resolve/main/README.md
496 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/Omega_WatchMoon_Square002_1328X1328.png
text: '-'
base_model: LAXMAYDAY/FLUX.2-dev-int8-tensorwise
instance_prompt: OmegaMoonWatch
license: apache-2.0
OmegaMoonWatch_Flux.2Dev

- Prompt
- -
Trigger words
You should use OmegaMoonWatch to trigger the image generation.
Download model
Download them in the Files & versions tab.