Instructions to use WaveCut/PixelWave_FLUX.1-schnell_04_SVDQuant-int4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/PixelWave_FLUX.1-schnell_04_SVDQuant-int4 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/PixelWave_FLUX.1-schnell_04_SVDQuant-int4", 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
- WIP - read P.S.
- Model Details
- P.S. Yields worse than expected generation results, so not recommended as for now, I will take another try to quantize it using slow mode.
- P.P.S. I've ran full quantization, but due to the way the toolset implemented, it had a bug at the very end in the eval part of workflow, so it exited with error not saving a single byte of final quantization result, everything is lost.
- Model Details
WIP - read P.S.
Model Details
Just the SVDQuant quantized int4 variant of the base model mikeyandfriends/PixelWave_FLUX.1-schnell_04.
It was quantized using official svdquant toolset using both fast and gptq presets.
P.S. Yields worse than expected generation results, so not recommended as for now, I will take another try to quantize it using slow mode.
P.P.S. I've ran full quantization, but due to the way the toolset implemented, it had a bug at the very end in the eval part of workflow, so it exited with error not saving a single byte of final quantization result, everything is lost.
Due to the fact that I paid for the compute myself I consider this loss of ~$60 as a valuable lesson, but I would not redo it again, as I am short on free cash atm. Sorry. Fot those who willing to have it done - feel free to generate a redeemable credit code at RunPod, and send it to me via telegram: t.me/WaveCut, and I'll be happy to get another shot at it.
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Model tree for WaveCut/PixelWave_FLUX.1-schnell_04_SVDQuant-int4
Base model
black-forest-labs/FLUX.1-schnell