Instructions to use harita001/realistic-pose-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use harita001/realistic-pose-test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Tongyi-MAI/Z-Image-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("harita001/realistic-pose-test") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
realistic-pose-test
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- Prompt
- -
Trigger words
You should use amateur digital snapshot to trigger the image generation.
You should use candid to trigger the image generation.
You should use smartphone capture to trigger the image generation.
You should use high ISO noise to trigger the image generation.
You should use direct on-camera flash to trigger the image generation.
Download model
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Model tree for harita001/realistic-pose-test
Base model
Tongyi-MAI/Z-Image-Turbo