Instructions to use seawolf2357/my-lora-20260110-0809 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use seawolf2357/my-lora-20260110-0809 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("seawolf2357/my-lora-20260110-0809") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Upload README.md with huggingface_hub
Browse files
README.md
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---
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license: apache-2.0
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tags:
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- lora
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- z-image
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- diffusers
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- text-to-image
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library_name: diffusers
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---
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# my-lora-20260110-0809
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LoRA Trainer로 학습된 커스텀 LoRA 모델
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## 모델 정보
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- **유형**: Z-Image용 LoRA 가중치
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- **생성일**: 2026-01-10 08:29:54
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- **트리거 워드**: `koyoon`
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## 사용 방법
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```python
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from diffusers import DiffusionPipeline
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pipe = DiffusionPipeline.from_pretrained("your-base-model")
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pipe.load_lora_weights("seawolf2357/my-lora-20260110-0809")
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pipe.to("cuda")
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prompt = "koyoon, your prompt here"
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image = pipe(prompt).images[0]
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```
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---
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*Z-Image LoRA Trainer로 생성됨*
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