Instructions to use xgreenspace/liminal1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xgreenspace/liminal1 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("xgreenspace/liminal1") prompt = "xxf" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from xgreenspace/liminal1: direct link, hf CLI and curl.
- Browser
- Download file 806 Bytes
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https://huggingface.co/xgreenspace/liminal1/resolve/main/README.md
- Command line
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hf download hf://xgreenspace/liminal1/README.md
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curl -L -o README.md https://huggingface.co/xgreenspace/liminal1/resolve/main/README.md
806 Bytes
metadata
tags:
- flux
- text-to-image
- lora
- diffusers
- fal
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: xxf
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
liminal1
Model description
First attempt at a liminal lora. This lora should produce liminal spaces that look like old photos.
Trigger words
You should use xxf 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.