Instructions to use yitongl/sparse_quant_exp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yitongl/sparse_quant_exp with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("yitongl/sparse_quant_exp", 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
| #SBATCH --job-name=sfp4-s0 | |
| #SBATCH --account=nvr_elm_llm | |
| #SBATCH --partition=interactive | |
| #SBATCH --nodes=1 | |
| #SBATCH --gres=gpu:1 | |
| #SBATCH --cpus-per-task=16 | |
| #SBATCH --mem=64G | |
| #SBATCH --time=00:30:00 | |
| #SBATCH --output=slurm_logs/sfp4_s0_%j.out | |
| #SBATCH --error=slurm_logs/sfp4_s0_%j.err | |
| set -ex | |
| cd /lustre/fsw/portfolios/nvr/projects/nvr_elm_llm/users/yitongl/code/FastVideo | |
| source .venv/bin/activate | |
| export PYTHONPATH=fastvideo-kernel/python:fastvideo-kernel:$PYTHONPATH | |
| export FASTVIDEO_ATTENTION_BACKEND=SPARSE_FP4_ATTN | |
| mkdir -p outputs_sfp4_s0 | |
| # Same prompt, seed, params as dense FP4 run | |
| fastvideo generate \ | |
| --model-path Wan-AI/Wan2.1-T2V-1.3B-Diffusers \ | |
| --sp-size 1 --tp-size 1 --num-gpus 1 \ | |
| --dit-cpu-offload False --vae-cpu-offload False \ | |
| --text-encoder-cpu-offload True --pin-cpu-memory False \ | |
| --height 480 --width 832 --num-frames 81 \ | |
| --num-inference-steps 50 --fps 16 \ | |
| --guidance-scale 6.0 --flow-shift 8.0 \ | |
| --prompt "Will Smith casually eats noodles, his relaxed demeanor contrasting with the energetic background of a bustling street food market. The scene captures a mix of humor and authenticity. Mid-shot framing, vibrant lighting." \ | |
| --seed 1024 \ | |
| --VSA-sparsity 0.0 \ | |
| --output-path outputs_sfp4_s0/ | |
| echo "=== Done ===" | |
| ls -lh outputs_sfp4_s0/*.mp4 | |
| echo "--- Dense FP4 reference ---" | |
| ls -lh outputs_dense_fp4/*.mp4 | |