Text-to-Image
Diffusers
Safetensors
English
Chinese
QwenImagePipeline
nf4
Abliterated
Qwen2.5-VL7b-Abliterated
instruct
Diffusers
Transformers
uncensored
image-to-image
image-generation
Instructions to use lhca521/QWEN_IMAGE_nf4_w_AbliteratedTE_Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lhca521/QWEN_IMAGE_nf4_w_AbliteratedTE_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("lhca521/QWEN_IMAGE_nf4_w_AbliteratedTE_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
QWEN_IMAGE_nf4_w_AbliteratedTE_Diffusers / text_encoder /VanillaQwen25VL_model-00004-of-00004.safetensors
- Xet hash:
- b71365de560a501a28cab9fa046ff664e957b85ca7dd2724c51dadc9368549ed
- Size of remote file:
- 1.69 GB
- SHA256:
- 5dd068336d14d45ffb43cef374d286cc6ba9d8741b028f90a7d040d847961f4a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.