Text-to-Image
Diffusers
Safetensors
ErnieImagePipeline
ernie-image
sdnq
quantized
uint4
static
quantized-matmul
Instructions to use WaveCut/ERNIE-Image-Turbo-SDNQ-uint4-static with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/ERNIE-Image-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/ERNIE-Image-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
- Draw Things
- DiffusionBee
| { | |
| "runtime": { | |
| "recommended_torch_cuda_alloc_conf": null, | |
| "avoid_torch_cuda_alloc_conf": [ | |
| "expandable_segments:True,max_split_size_mb:32" | |
| ], | |
| "keep_model_resident": true, | |
| "avoid_empty_cache_between_generations": true, | |
| "use_pe_for_image_benchmarks": false | |
| }, | |
| "sdnq": { | |
| "requires_explicit_apply_quantized_matmul": true, | |
| "apply_quantized_matmul_components": [ | |
| "pe", | |
| "text_encoder", | |
| "transformer" | |
| ], | |
| "apply_quantized_matmul_function": "sdnq.loader.apply_sdnq_options_to_model(component, use_quantized_matmul=True)" | |
| }, | |
| "validated": { | |
| "device": "NVIDIA RTX 6000 Ada Generation", | |
| "torch": "2.8.0+cu128", | |
| "sdnq": "0.1.9", | |
| "num_inference_steps": 8, | |
| "guidance_scale": 1.0, | |
| "use_pe": false | |
| }, | |
| "metrics": { | |
| "explicit_quantized_matmul_default_allocator": "metrics/ernie_uint4_qmm_explicit_default_allocator_8step_metrics.json", | |
| "allocator_debug": "metrics/runtime_allocator_debug_metrics.json" | |
| } | |
| } | |