Instructions to use hf-internal-testing/civitai-light-shadow-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/civitai-light-shadow-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("gsdf/Counterfeit-V2.5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("hf-internal-testing/civitai-light-shadow-lora") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
This repository contains a LoRA model downloaded from CivitAI.
You can load this checkpoint in 🧨 diffusers and perform like so:
import torch
from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
pipeline = StableDiffusionPipeline.from_pretrained(
"gsdf/Counterfeit-V2.5", torch_dtype=torch.float16, safety_checker=None
).to("cuda")
pipeline.scheduler = DPMSolverMultistepScheduler.from_config(
pipeline.scheduler.config, use_karras_sigmas=True
)
pipeline.load_lora_weights(
"sayakpaul/civitai-light-shadow-lora", weight_name="light_and_shadow.safetensors"
)
prompt = "masterpiece, best quality, 1girl, at dusk"
negative_prompt = ("(low quality, worst quality:1.4), (bad anatomy), (inaccurate limb:1.2), "
"bad composition, inaccurate eyes, extra digit, fewer digits, (extra arms:1.2), large breasts")
image = pipeline(prompt=prompt,
negative_prompt=negative_prompt,
width=512,
height=768,
num_inference_steps=15,
generator=torch.manual_seed(0)
).images[0]
image.save("image.png")
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