metadata
base_model: neonforestmist/Clover-Image-Tiny
library_name: diffusers
license: creativeml-openrail-m
inference: true
datasets:
- neonforestmist/GPT_Monet_Style_Images
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- lora
- clover-image
Clover Image Tiny — Monet LoRA
A rank-16 style LoRA trained on
neonforestmist/GPT_Monet_Style_Images
for neonforestmist/Clover-Image-Tiny.
Use the prompt trigger Monet Style.
import torch
from diffusers import DiffusionPipeline
pipe = DiffusionPipeline.from_pretrained(
"neonforestmist/Clover-Image-Tiny",
torch_dtype=torch.float16,
).to("cuda")
pipe.load_lora_weights("neonforestmist/clover-image-tiny-monet-lora")
image = pipe(
"Monet Style, a small blue cat resting beside a lily pond",
num_inference_steps=20,
guidance_scale=7.5,
).images[0]
Examples
Training
- Base revision:
63b0e9f6be9c00888ff464f342a9ef052bf76681 - Dataset revision:
2941a88e5268bbb4224ff2916013b78ec313d03a - Resolution: 512 × 512
- Optimizer steps: 1,000
- Rank: 16
- Batch size: 1
- Learning rate: 1e-4 with cosine decay and 100 warmup steps
- Min-SNR gamma: 5
- Precision: fp16
- Seed: 20260730
- Trainer: Diffusers 0.39.0
train_text_to_image_lora.py
The reproducible job configuration is included in the Clover source
repository under training/.
License and limitations
These adapter weights are a derivative of Clover Image Tiny and use the CreativeML Open RAIL-M license. The training dataset is Apache-2.0. Generated content can inherit limitations and biases from the base checkpoint and training data; review outputs before use.