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 Settings
- Draw Things
- DiffusionBee
Download assets/comparison/comparison_grid_1to1_q98.webp from WaveCut/Lens-Turbo-SDNQ-uint4-static: direct link, hf CLI and curl.
- Browser
- Download file 6.28 MB
-
https://huggingface.co/WaveCut/Lens-Turbo-SDNQ-uint4-static/resolve/main/assets/comparison/comparison_grid_1to1_q98.webp
- Command line
-
hf download hf://WaveCut/Lens-Turbo-SDNQ-uint4-static/assets/comparison/comparison_grid_1to1_q98.webp
-
curl -L -o comparison_grid_1to1_q98.webp https://huggingface.co/WaveCut/Lens-Turbo-SDNQ-uint4-static/resolve/main/assets/comparison/comparison_grid_1to1_q98.webp
6.28 MB

- Xet hash:
- 756c472e5eae45895883527bbcbff03cc70bea16afcafafebd765cfeb626ba70
- Size of remote file:
- 6.28 MB
- SHA256:
- b8b80cc6277ead0a25edd9f4de8f5d8ec77f17dcce3d5025b0118e587df09cf4
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