Instructions to use nlobak/2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nlobak/2 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("nlobak/2") prompt = "sitting on a roof looking on the big city, dressed simple but elegant" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
|
Download README.md from nlobak/2: direct link, hf CLI and curl.
- Browser
- Download file 820 Bytes
-
https://huggingface.co/nlobak/2/resolve/main/README.md
- Command line
-
hf download hf://nlobak/2/README.md
-
curl -L -o README.md https://huggingface.co/nlobak/2/resolve/main/README.md
820 Bytes
metadata
tags:
- flux
- text-to-image
- lora
- diffusers
- fal
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: sitting on a roof looking on the big city, dressed simple but elegant
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
2
Model description
Trigger words
You should use sitting on a roof looking on the big city, dressed simple but elegant to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Training at fal.ai
Training was done using fal.ai/models/fal-ai/flux-lora-fast-training.