Text-to-Image
Diffusers
OpenVINO
StableDiffusionPipeline
int4
optimum
optimum-intel
nncf
lcm
anime
sd1.5
cpu
Instructions to use HelloSun/animemixv10_lcm-OpenVINO-INT4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use HelloSun/animemixv10_lcm-OpenVINO-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("HelloSun/animemixv10_lcm-OpenVINO-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 Settings
- Draw Things
- DiffusionBee
Commit History
27 days ago
-
docs: restructure README/REPORT and clean metadata
- README: add TOC, quick-facts table, install/usage/parameters, file map, known limitations and licence section; split the benchmarked examples from the un-benchmarked style gallery - README: report model sizes from the actual Git-LFS byte counts instead of rounded hand-written figures - README: state explicitly that add 30 more crossover prompts to the tables; document that generate5.py only ships 10 of the 40 benchmarked prompts - REPORT: convert dense bullet lists into proper tables, add a TOC, per-step timings, and an observations section - Replace benchmark numbers that disagreed with the benchmark JSON - model_index.json / */config.json: replace leaked build-host paths with the upstream repo id - benchmark.json: use the HF repo id and repo-relative image paths - benchmark_quantization.json: drop local build directories - examples/prompts.txt: strip leftover timestamps - scripts: replace hardcoded /home/user/app and /tmp paths with relative defaults and the real repo i…e4dbd79 -
Add AnimeMix v10 LCM OpenVINO INT4: model + 10 examples + README/REPORT/scripts
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