Instructions to use danielpleus/daniel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use danielpleus/daniel 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("danielpleus/daniel") prompt = "a D4N1EL man in a bustling cafe " image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 958 Bytes
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base_model: black-forest-labs/FLUX.1-dev
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
tags:
- autotrain
- spacerunner
- text-to-image
- flux
- lora
- diffusers
- template:sd-lora
widget:
- text: 'a D4N1EL man in a bustling cafe '
output:
url: samples/1725022967280__000001000_0.jpg
- text: a D4N1EL man in front of the eiffel tower
output:
url: samples/1725023069721__000001000_1.jpg
- text: a D4N1EL man in hamburg
output:
url: samples/1725023172072__000001000_2.jpg
instance_prompt: D4N1EL
---
# daniel
Model trained with [AI Toolkit by Ostris](https://github.com/ostris/ai-toolkit)
<Gallery />
## Trigger words
You should use `D4N1EL` to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
[Download](/danielpleus/daniel/tree/main) them in the Files & versions tab.
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