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
| { | |
| "model": "WaveCut/ERNIE-Image-Turbo-SDNQ-uint4-static", | |
| "device": "NVIDIA RTX 6000 Ada Generation", | |
| "torch": "2.8.0+cu128", | |
| "cases": [ | |
| { | |
| "run": "warmup", | |
| "prompt_id": "00-cyrillic-poster", | |
| "width": 1024, | |
| "height": 1024, | |
| "seconds": 42.33458385616541, | |
| "stage_seconds_sum": 41.638948045670986, | |
| "unattributed_seconds": 0.6956358104944229, | |
| "gpu_start_mib": 10172, | |
| "gpu_end_mib": 15368, | |
| "torch_peak_allocated_mib": 12175, | |
| "torch_peak_reserved_mib": 14848, | |
| "stages": { | |
| "pe.forward": { | |
| "seconds": 24.21831013262272, | |
| "calls": 415 | |
| }, | |
| "text_encoder.forward": { | |
| "seconds": 0.04355049878358841, | |
| "calls": 1 | |
| }, | |
| "transformer.forward": { | |
| "seconds": 17.202288791537285, | |
| "calls": 8 | |
| }, | |
| "vae.decode": { | |
| "seconds": 0.1747986227273941, | |
| "calls": 1 | |
| } | |
| }, | |
| "use_quantized_matmul": false, | |
| "image": "/root/ernie-qmm-debug/00-cyrillic-poster_noqmm_warmup.png" | |
| }, | |
| { | |
| "run": "hot_repeat", | |
| "prompt_id": "00-cyrillic-poster", | |
| "width": 1024, | |
| "height": 1024, | |
| "seconds": 24.803174294531345, | |
| "stage_seconds_sum": 24.33856651186943, | |
| "unattributed_seconds": 0.4646077826619148, | |
| "gpu_start_mib": 10278, | |
| "gpu_end_mib": 15318, | |
| "torch_peak_allocated_mib": 12175, | |
| "torch_peak_reserved_mib": 14798, | |
| "stages": { | |
| "pe.forward": { | |
| "seconds": 16.506547823548317, | |
| "calls": 421 | |
| }, | |
| "text_encoder.forward": { | |
| "seconds": 0.040486179292201996, | |
| "calls": 1 | |
| }, | |
| "transformer.forward": { | |
| "seconds": 7.632116124033928, | |
| "calls": 8 | |
| }, | |
| "vae.decode": { | |
| "seconds": 0.15941638499498367, | |
| "calls": 1 | |
| } | |
| }, | |
| "use_quantized_matmul": false, | |
| "image": "/root/ernie-qmm-debug/00-cyrillic-poster_noqmm_hot_repeat.png" | |
| }, | |
| { | |
| "run": "warmup", | |
| "prompt_id": "02-technical-diagram", | |
| "width": 1200, | |
| "height": 896, | |
| "seconds": 94.24524058401585, | |
| "stage_seconds_sum": 92.17488968372345, | |
| "unattributed_seconds": 2.0703509002923965, | |
| "gpu_start_mib": 10278, | |
| "gpu_end_mib": 15912, | |
| "torch_peak_allocated_mib": 12259, | |
| "torch_peak_reserved_mib": 15392, | |
| "stages": { | |
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| "seconds": 80.31031914055347, | |
| "calls": 2048 | |
| }, | |
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| "calls": 1 | |
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| "vae.decode": { | |
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| "calls": 1 | |
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| "use_quantized_matmul": false, | |
| "image": "/root/ernie-qmm-debug/02-technical-diagram_noqmm_warmup.png" | |
| }, | |
| { | |
| "run": "hot_repeat", | |
| "prompt_id": "02-technical-diagram", | |
| "width": 1200, | |
| "height": 896, | |
| "seconds": 94.40739246457815, | |
| "stage_seconds_sum": 92.33396648615599, | |
| "unattributed_seconds": 2.073425978422165, | |
| "gpu_start_mib": 10278, | |
| "gpu_end_mib": 15910, | |
| "torch_peak_allocated_mib": 12259, | |
| "torch_peak_reserved_mib": 15390, | |
| "stages": { | |
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| "seconds": 80.37759981304407, | |
| "calls": 2048 | |
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| "calls": 8 | |
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| "vae.decode": { | |
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| "use_quantized_matmul": false, | |
| "image": "/root/ernie-qmm-debug/02-technical-diagram_noqmm_hot_repeat.png" | |
| }, | |
| { | |
| "run": "warmup", | |
| "prompt_id": "00-cyrillic-poster", | |
| "width": 1024, | |
| "height": 1024, | |
| "seconds": 47.86481238901615, | |
| "stage_seconds_sum": 47.40215189009905, | |
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| "torch_peak_reserved_mib": 14832, | |
| "stages": { | |
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| "calls": 408 | |
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| "use_quantized_matmul": true, | |
| "image": "/root/ernie-qmm-debug/00-cyrillic-poster_qmm_warmup.png" | |
| }, | |
| { | |
| "run": "hot_repeat", | |
| "prompt_id": "00-cyrillic-poster", | |
| "width": 1024, | |
| "height": 1024, | |
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| "use_quantized_matmul": true, | |
| "image": "/root/ernie-qmm-debug/00-cyrillic-poster_qmm_hot_repeat.png" | |
| }, | |
| { | |
| "run": "warmup", | |
| "prompt_id": "02-technical-diagram", | |
| "width": 1200, | |
| "height": 896, | |
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| "stages": { | |
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| "calls": 2048 | |
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| "use_quantized_matmul": true, | |
| "image": "/root/ernie-qmm-debug/02-technical-diagram_qmm_warmup.png" | |
| }, | |
| { | |
| "run": "hot_repeat", | |
| "prompt_id": "02-technical-diagram", | |
| "width": 1200, | |
| "height": 896, | |
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| "calls": 638 | |
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| "image": "/root/ernie-qmm-debug/02-technical-diagram_qmm_hot_repeat.png" | |
| } | |
| ], | |
| "sdnq": "0.1.9" | |
| } | |