Text-to-Image
Diffusers
Safetensors
LensPipeline
lens
sdnq
uint4
static-quantization
ablation
model-cpu-offload
Instructions to use WaveCut/Lens-SDNQ-uint4-static with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/Lens-SDNQ-uint4-static with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WaveCut/Lens-SDNQ-uint4-static", 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
File size: 133 Bytes
9a16379 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:16ff57dc58c48f438e786bd41502a2f5aa36646f55763cdc3b3e6d957cf46dc5
size 16108834
|