Text-to-Image
Diffusers
Safetensors
English
Russian
LensPipeline
LensPipeline
sdnq
quantized
uint4
static-quantization
ablation
Instructions to use WaveCut/Lens-Turbo-SDNQ-uint4-static with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/Lens-Turbo-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-Turbo-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
- Draw Things
- DiffusionBee
- Xet hash:
- 9ea86e9274aee7318c9651cb2eee04f9fc45415dc62818eff23fdcb0aa497112
- Size of remote file:
- 27.9 MB
- SHA256:
- 928addc4a139e5382c06af49ebd495a4aa2aca99d13b872873e27bcbacc3ae4d
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