Text-to-Image
Diffusers
English
Arabic
stable-diffusion-xl
sdxl
lora
king2
arabic
art
image-generation
fal-ai
Instructions to use RASHID778/king2-image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RASHID778/king2-image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("RASHID778/king2-image") prompt = "a futuristic royal palace at sunset, highly detailed, 8k, golden hour, epic composition" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
KING2-IMAGE: SDXL LoRA trained on text-to-image-2M subset (Kaggle)
Browse files- README.md +35 -0
- checkpoint-1000/optimizer.bin +3 -0
- checkpoint-1000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-1000/random_states_0.pkl +3 -0
- checkpoint-1000/scaler.pt +3 -0
- checkpoint-1000/scheduler.bin +3 -0
- checkpoint-1500/optimizer.bin +3 -0
- checkpoint-1500/pytorch_lora_weights.safetensors +3 -0
- checkpoint-1500/random_states_0.pkl +3 -0
- checkpoint-1500/scaler.pt +3 -0
- checkpoint-1500/scheduler.bin +3 -0
- checkpoint-500/optimizer.bin +3 -0
- checkpoint-500/pytorch_lora_weights.safetensors +3 -0
- checkpoint-500/random_states_0.pkl +3 -0
- checkpoint-500/scaler.pt +3 -0
- checkpoint-500/scheduler.bin +3 -0
- pytorch_lora_weights.safetensors +3 -0
README.md
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---
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license: openrail++
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base_model: stabilityai/stable-diffusion-xl-base-1.0
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library_name: diffusers
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tags:
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- text-to-image
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- stable-diffusion-xl
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- lora
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- diffusers
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- king2
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pipeline_tag: text-to-image
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---
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# ًں‘‘ KING2-IMAGE
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SDXL LoRA (rank 16) ظ…ط¯ط±ظ‘ط¨ ط¹ظ„ظ‰ ط¹ظٹظ‘ظ†ط© ظ…ظ† `jackyhate/text-to-image-2M` — ظ…ظˆط¯ظٹظ„ ط§ظ„طµظˆط± ط§ظ„ط®ط§طµ ط¨ظ…ظ†طµط© KING2.
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## Usage
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```python
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import torch
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from diffusers import DiffusionPipeline
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pipe = DiffusionPipeline.from_pretrained(
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"stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
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).to("cuda")
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pipe.load_lora_weights("RASHID778/king2-image")
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image = pipe("a futuristic royal palace at sunset, highly detailed, 8k").images[0]
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```
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## Training
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- Base: `stabilityai/stable-diffusion-xl-base-1.0` + `madebyollin/sdxl-vae-fp16-fix`
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- Data: 3000 طµظˆط±ط© ظ…ظ† `jackyhate/text-to-image-2M`
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- 1500 ط®ط·ظˆط©طŒ resolution 768طŒ rank 16طŒ lr 1e-4 cosineطŒ fp16
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size 48485733
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checkpoint-500/pytorch_lora_weights.safetensors
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