Instructions to use rmaxvell/ots with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rmaxvell/ots with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ostris/OpenFLUX.1", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("rmaxvell/ots") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from rmaxvell/ots: direct link, hf CLI and curl.
- Browser
- Download file 367 Bytes
-
https://huggingface.co/rmaxvell/ots/resolve/main/README.md
- Command line
-
hf download hf://rmaxvell/ots/README.md
-
curl -L -H "Authorization: Bearer $HF_TOKEN" -o README.md https://huggingface.co/rmaxvell/ots/resolve/main/README.md
367 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: '-'
output:
url: images/a3e91458.jpg
base_model: ostris/OpenFLUX.1
instance_prompt: null
ots

- Prompt
- -
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.