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harpomaxx/deeplili
deeplili is a text-to-image model from harpomaxx. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as creativeml-openrail-m.
This is a fine tuned model of stable-diffusion-v1-4 for creating images in the style of great artist, Lili Fiallo. Click here more about Lili Fiallo work of art.
Downloads · 30 days
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.safetensors9.7 GB · 50%
From the Hugging Face model README
This is a fine tuned model of stable-diffusion-v1-4 for creating images in the style of great artist, Lili Fiallo. Click here more about Lili Fiallo work of art.
Use the tokens sks style in your prompts for the effect.
Model was trained using the diffusers library, which based on Dreambooth implementation. Training steps included:
accelerate launch train_dreambooth.py \
--pretrained_model_name_or_path=$MODEL_NAMEi \
--instance_data_dir=$INSTANCE_DIR \
--class_data_dir=$CLASS_DIR \
--output_dir=$OUTPUT_DIR \
--instance_prompt="sks style" \
--resolution=512 \
--train_batch_size=1 \
--gradient_accumulation_steps=1 \
--gradient_checkpointing \
--use_8bit_adam \
--enable_xformers_memory_efficient_attention \
--set_grads_to_none \
--learning_rate=1e-6 \
--lr_scheduler="constant" \
--lr_warmup_steps=0 \
--max_train_steps=2000 \
--train_text_encoder \
--mixed_precision=fp16
This model can be used just like any other Stable Diffusion model. For more information, please have a look at the Stable Diffusion.
You can also export the model to ONNX, MPS and/or FLAX/JAX.
#!pip install diffusers transformers scipy torch
from diffusers import StableDiffusionPipeline
import torch
model_id = "harpomaxx/deeplili"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")
prompt = ", sks style"
image = pipe(prompt).images[0]
image.save("./example_output.png")



This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage. The CreativeML OpenRAIL License specifies: