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
Upload dataset/scaleup_api.py with huggingface_hub
Browse files- dataset/scaleup_api.py +1 -1
dataset/scaleup_api.py
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@@ -5,7 +5,7 @@ import argparse
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import torch
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from tqdm import tqdm
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ROOT_DIR = os.environ.get("ROOT_DIR", "
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QWEN_MODEL_PATH = "Qwen/Qwen2.5-VL-3B-Instruct"
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SYSTEM_PROMPT = """You are an expert image captioner.
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import torch
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from tqdm import tqdm
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ROOT_DIR = os.environ.get("ROOT_DIR", "Dataset_Directory")
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QWEN_MODEL_PATH = "Qwen/Qwen2.5-VL-3B-Instruct"
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SYSTEM_PROMPT = """You are an expert image captioner.
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