import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("comp646/hearthstone-sd15-lora")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Hearthstone SD 1.5 LoRA
This repository contains a Stable Diffusion 1.5 LoRA adapter trained for Hearthstone-style card artwork generation as part of the COMP 646 HearthGen project.
Files
pytorch_lora_weights.safetensors: Diffusers-compatible LoRA weights.
Intended Use
This model is intended for research and course-project reproduction. It is used by the HearthGen pipeline to compare:
- Stable Diffusion 1.5 text-only generation
- Stable Diffusion 1.5 with reference conditioning
- Stable Diffusion 1.5 + Hearthstone LoRA text-only generation
- Stable Diffusion 1.5 + Hearthstone LoRA with KG-retrieved reference conditioning
Loading With Diffusers
import torch
from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained(
"stable-diffusion-v1-5/stable-diffusion-v1-5",
torch_dtype=torch.float16,
).to("cuda")
pipe.load_lora_weights("comp646/hearthstone-sd15-lora")
image = pipe(
"hsart Hearthstone card art, Warrior minion, iron armor, glowing embers",
num_inference_steps=30,
guidance_scale=7.5,
).images[0]
Dataset
The LoRA was trained from the project artwork dataset:
comp646/hearthstone-art-512
The dataset contains Hearthstone artwork crops and metadata for project reproduction. Artwork and Hearthstone IP belong to Blizzard Entertainment; this model is distributed only for academic project use.
Project
Repository:
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Model tree for comp646/hearthstone-sd15-lora
Base model
stable-diffusion-v1-5/stable-diffusion-v1-5