Instructions to use chriswang2025/test-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use chriswang2025/test-lora 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("chriswang2025/test-lora") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
|
Download README.md from chriswang2025/test-lora: direct link, hf CLI and curl.
- Browser
- Download file 878 Bytes
-
https://huggingface.co/chriswang2025/test-lora/resolve/main/README.md
- Command line
-
hf download hf://chriswang2025/test-lora/README.md
-
curl -L -o README.md https://huggingface.co/chriswang2025/test-lora/resolve/main/README.md
878 Bytes
metadata
library_name: diffusers
base_model: black-forest-labs/FLUX.1-dev
tags:
- lora
- flux
- text-to-image
license: mit
LoRA Model: AldaraLora_Civitai_FLUX_Wave_V3_2
Test LoRA model exported from API server
Usage
Trigger Word
Use the following trigger word in your prompts:
AldaraLora_Civitai_FLUX_Wave_V3_2
Example
from diffusers import DiffusionPipeline
import torch
pipe = DiffusionPipeline.from_pretrained(
"black-forest-labs/FLUX.1-dev",
torch_dtype=torch.float16
)
pipe.load_lora_weights("chriswang2025/chris")
prompt = "AldaraLora_Civitai_FLUX_Wave_V3_2, a beautiful landscape"
image = pipe(prompt).images[0]
image.save("output.png")
Model Details
- Trigger Word:
AldaraLora_Civitai_FLUX_Wave_V3_2 - Base Model: FLUX.1-dev
- Type: LoRA (Low-Rank Adaptation)
- Version: 1.0
License
MIT License