Instructions to use glif-loradex-trainer/dham_dham_roadside with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use glif-loradex-trainer/dham_dham_roadside with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("glif-loradex-trainer/dham_dham_roadside") prompt = "TOK robot" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- diffusers
- text-to-image
- template:sd-lora
- base_model:black-forest-labs/FLUX.1-dev
- base_model:finetune:black-forest-labs/FLUX.1-dev
- license:other
- region:us
- flux
- lora
widget:
- output:
url: samples/1731452738668__000003000_0.jpg
text: TOK robot
- output:
url: samples/1731452760864__000003000_1.jpg
text: TOK gengar
- output:
url: samples/1731452783084__000003000_2.jpg
text: TOK hair salon
- output:
url: samples/1731452805298__000003000_3.jpg
text: TOK monstertruck show
- output:
url: samples/1731452827518__000003000_4.jpg
text: TOK eiffel tower
base_model: black-forest-labs/FLUX.1-dev
trigger: TOK
instance_prompt: TOK
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
dham_roadside
Model trained with AI Toolkit by Ostris under the Glif Loradex program by Glif user dham.

- Prompt
- TOK robot

- Prompt
- TOK gengar

- Prompt
- TOK hair salon

- Prompt
- TOK monstertruck show

- Prompt
- TOK eiffel tower
Trigger words
You should use TOK to trigger the image generation.
Download model
Weights for this model are available in Safetensors format. Download them in the Files & versions tab.
License
This model is licensed under the flux-1-dev-non-commercial-license.