import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("climba/MinorPerception-R2I-LoRA")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]MinorPerception R2I LoRA Adapters
This repository contains selected LoRA adapters from the MinorPerception R2I diffusion experiments. The base model weights are not included.
Contents
sd35_v3_qwenvl_hybrid_grpo_lora/- Selected Stable Diffusion 3.5 LoRA from the Qwen-VL hybrid GRPO reward experiment.
- Intended base model:
stabilityai/stable-diffusion-3.5-medium.
flux_v3_clip_grpo_stage3init_memfix_lora/- Selected FLUX LoRA from the stage3 warm-start, memory-fixed CLIP-GRPO experiment.
- Intended base model:
black-forest-labs/FLUX.1-dev.
Notes
These adapters were trained for R2I-style prompt-to-resolved-caption alignment experiments. They are experimental research artifacts and should be evaluated against the exact inference scripts and prompts used in the repository.
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