Instructions to use WaveCut/sdxs-2b-sdnq-t4-tebf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/sdxs-2b-sdnq-t4-tebf16 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/sdxs-2b-sdnq-t4-tebf16", 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
| { | |
| "source": "/root/sdxs-sdnq-lab/upstream", | |
| "source_model": "AiArtLab/sdxs-2b", | |
| "variant": "t4-tebf16", | |
| "repo_suffix": "sdxs-2b-sdnq-t4-tebf16", | |
| "description": "Cosmos transformer uint4, text encoder bf16, VAE bf16.", | |
| "timings": { | |
| "load_seconds": 12.35, | |
| "quantize_transformer_seconds": 0.962, | |
| "save_seconds": 4.913, | |
| "total_seconds": 18.229 | |
| }, | |
| "cuda_mem_final": { | |
| "allocated_gb": 3.0434, | |
| "reserved_gb": 3.125, | |
| "peak_allocated_gb": 5.6538 | |
| }, | |
| "components": { | |
| "transformer": { | |
| "layers": { | |
| "uint4": 442 | |
| }, | |
| "weight_elements": { | |
| "uint4": 965738496 | |
| }, | |
| "class": "CosmosTransformer3DModel", | |
| "target_dtype": "uint4", | |
| "cuda_mem_after": { | |
| "allocated_gb": 3.0434, | |
| "reserved_gb": 3.125, | |
| "peak_allocated_gb": 5.6538 | |
| } | |
| } | |
| }, | |
| "output_size_bytes": 3237051220, | |
| "output_size_gb": 3.0147 | |
| } | |