Instructions to use hcickje/plswork with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hcickje/plswork 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("hcickje/plswork") prompt = "in the style of ilys" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from hcickje/plswork: direct link, hf CLI and curl.
- Browser
- Download file 555 Bytes
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https://huggingface.co/hcickje/plswork/resolve/main/README.md
- Command line
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hf download hf://hcickje/plswork/README.md
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curl -L -o README.md https://huggingface.co/hcickje/plswork/resolve/main/README.md
555 Bytes
metadata
tags:
- flux
- text-to-image
- lora
- diffusers
- fal
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: in the style of ilys
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
flux lora illustration v1
Model description
Trigger words
You should use in the style of ilys to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Training at fal.ai
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