Instructions to use Gerchegg/hyphoria_qwen_v1-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Gerchegg/hyphoria_qwen_v1-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Gerchegg/hyphoria_qwen_v1-Diffusers", 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 Settings
- Draw Things
- DiffusionBee
Hyphoria Qwen v1 Diffusers
Diffusers-packaged version of chapel/hyphoria_qwen_v1.0
using hyphoria_qwen_v1_bf16.safetensors as the custom Qwen-Image transformer.
Packaged analogously to Gerchegg/Qwen_FloVector_Hex_CharactersScenes_V1-Diffusers:
- base components from
Qwen/Qwen-Image:scheduler/,text_encoder/,tokenizer/,vae/ - custom transformer weights at
transformer/diffusion_pytorch_model.safetensors - Qwen-Image transformer config at
transformer/config.json
Source checkpoint: https://huggingface.co/chapel/hyphoria_qwen_v1.0
- Downloads last month
- 3
Model tree for Gerchegg/hyphoria_qwen_v1-Diffusers
Base model
Qwen/Qwen-Image