Instructions to use VHKE/sprbtc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use VHKE/sprbtc 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("VHKE/sprbtc") prompt = "SPRBTC mega sport biotic bottle on a night stand --d 45" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- flux
- lora
- diffusers
- template:sd-lora
- fluxgym
widget:
- output:
url: sample/sprbtc_000500_01_20250305052012_45.png
text: SPRBTC mega sport biotic bottle on a night stand --d 45
- output:
url: sample/sprbtc_001000_01_20250305052908_45.png
text: SPRBTC mega sport biotic bottle placed on a table --d 45
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: SPRBTC
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
SPRBTC
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- SPRBTC mega sport biotic bottle on a night stand --d 45

- Prompt
- SPRBTC mega sport biotic bottle placed on a table --d 45
Trigger words
You should use SPRBTC to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, Forge, etc.
Weights for this model are available in Safetensors format.