Instructions to use lember/aigaci-dev2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lember/aigaci-dev2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("undefined", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lember/aigaci-dev2") prompt = "aigaci" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from lember/aigaci-dev2: direct link, hf CLI and curl.
- Browser
- Download file 570 Bytes
-
https://huggingface.co/lember/aigaci-dev2/resolve/main/README.md
- Command line
-
hf download hf://lember/aigaci-dev2/README.md
-
curl -L -o README.md https://huggingface.co/lember/aigaci-dev2/resolve/main/README.md
570 Bytes
metadata
tags:
- flux
- text-to-image
- lora
- diffusers
- fal
base_model: undefined
instance_prompt: aigaci
license: other
aigaci dev2
Model description
desc
Trigger words
You should use aigaci 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-portrait-trainer.