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
| 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[@]}" | |