Text-to-Image
Diffusers
Safetensors
StableDiffusionXLPipeline
stable-diffusion-xl
stable-diffusion-xl-diffusers
Instructions to use Chenhsing/sdxl-part-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Chenhsing/sdxl-part-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Chenhsing/sdxl-part-model", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
YAML Metadata Error:"base_model" with value "/mnt/blob/stable-diffusion-xl-base-1.0" is not valid. Use a model id from https://hf.co/models.
Text-to-image finetuning - Chenhsing/sdxl-part-model
This pipeline was finetuned from /mnt/blob/stable-diffusion-xl-base-1.0 on the lambdalabs/pokemon-blip-captions dataset. Below are some example images generated with the finetuned pipeline using the following prompt: A jeep car is moving on the snow.:
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
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