Image-to-Image
Diffusers
Safetensors
image-decomposition
layered-image-editing
diffusion
flux
lora
transparent-rgba
Instructions to use SynLayers/synlayers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SynLayers/synlayers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("SynLayers/synlayers") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
File size: 2,753 Bytes
20cd16f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 | #!/usr/bin/env bash
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
PYTHON_BIN="${PYTHON_BIN:-python}"
: "${BLENDED_DIR:?Set BLENDED_DIR}"
: "${LAION_DIR:?Set LAION_DIR}"
: "${CAPTION_DIR:?Set CAPTION_DIR}"
: "${OUTPUT_DIR:?Set OUTPUT_DIR}"
CAPTION_META="${CAPTION_META:-${CAPTION_DIR}/captions.jsonl}"
NUM_SAMPLES="${NUM_SAMPLES:-500000}"
START_INDEX="${START_INDEX:-0}"
SEED="${SEED:-42}"
MAX_BASE_SAMPLES="${MAX_BASE_SAMPLES:-18000}"
MIN_DONOR_SAMPLES="${MIN_DONOR_SAMPLES:-1}"
MAX_DONOR_SAMPLES="${MAX_DONOR_SAMPLES:-4}"
MIN_LAYERS_PER_DONOR="${MIN_LAYERS_PER_DONOR:-0}"
MAX_LAYERS_PER_DONOR="${MAX_LAYERS_PER_DONOR:-2}"
MIN_LAYERS_TO_REMOVE="${MIN_LAYERS_TO_REMOVE:-1}"
MAX_LAYERS_TO_REMOVE="${MAX_LAYERS_TO_REMOVE:-4}"
ADDED_LAYER_MIN_SIZE="${ADDED_LAYER_MIN_SIZE:-0.9}"
ADDED_LAYER_MAX_SIZE="${ADDED_LAYER_MAX_SIZE:-1.1}"
LAION_PROB="${LAION_PROB:-0.60}"
CAPTION_PROB="${CAPTION_PROB:-0.35}"
LAION_MIN_SIZE="${LAION_MIN_SIZE:-0.3}"
LAION_MAX_SIZE="${LAION_MAX_SIZE:-0.4}"
CAPTION_MIN_SIZE="${CAPTION_MIN_SIZE:-0.6}"
CAPTION_MAX_SIZE="${CAPTION_MAX_SIZE:-0.8}"
ALPHAVAE_MIN_LAYERS="${ALPHAVAE_MIN_LAYERS:-0}"
ALPHAVAE_MAX_LAYERS="${ALPHAVAE_MAX_LAYERS:-0}"
ALPHAVAE_MIN_SIZE="${ALPHAVAE_MIN_SIZE:-0.25}"
ALPHAVAE_MAX_SIZE="${ALPHAVAE_MAX_SIZE:-0.40}"
NUM_WORKERS="${NUM_WORKERS:-64}"
SKIP_EXISTING="${SKIP_EXISTING:-0}"
cmd=(
"$PYTHON_BIN" "$SCRIPT_DIR/scaleup_dataset.py"
--blended_dir "$BLENDED_DIR"
--laion_dir "$LAION_DIR"
--caption_dir "$CAPTION_DIR"
--caption_meta "$CAPTION_META"
--output_dir "$OUTPUT_DIR"
--num_samples "$NUM_SAMPLES"
--start_index "$START_INDEX"
--seed "$SEED"
--min_donor_samples "$MIN_DONOR_SAMPLES"
--max_donor_samples "$MAX_DONOR_SAMPLES"
--min_layers_per_donor "$MIN_LAYERS_PER_DONOR"
--max_layers_per_donor "$MAX_LAYERS_PER_DONOR"
--added_layer_min_size "$ADDED_LAYER_MIN_SIZE"
--added_layer_max_size "$ADDED_LAYER_MAX_SIZE"
--laion_prob "$LAION_PROB"
--caption_prob "$CAPTION_PROB"
--laion_min_size "$LAION_MIN_SIZE"
--laion_max_size "$LAION_MAX_SIZE"
--caption_min_size "$CAPTION_MIN_SIZE"
--caption_max_size "$CAPTION_MAX_SIZE"
--min_layers_to_remove "$MIN_LAYERS_TO_REMOVE"
--max_layers_to_remove "$MAX_LAYERS_TO_REMOVE"
--alphavae_min_layers "$ALPHAVAE_MIN_LAYERS"
--alphavae_max_layers "$ALPHAVAE_MAX_LAYERS"
--alphavae_min_size "$ALPHAVAE_MIN_SIZE"
--alphavae_max_size "$ALPHAVAE_MAX_SIZE"
--max_base_samples "$MAX_BASE_SAMPLES"
--num_workers "$NUM_WORKERS"
)
if [[ -n "${ALPHAVAE_DIR:-}" ]]; then
cmd+=(--alphavae_dir "$ALPHAVAE_DIR")
fi
if [[ -n "${ALPHAVAE_PROMPTS:-}" ]]; then
cmd+=(--alphavae_prompts "$ALPHAVAE_PROMPTS")
fi
if [[ "$SKIP_EXISTING" == "1" ]]; then
cmd+=(--skip_existing)
fi
"${cmd[@]}"
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