Text-to-Image
Diffusers
Safetensors
image-to-image
quantization
w4a4
svdquant
gptq
nunchaku
8-bit precision
Instructions to use ModelsLab/Qwen-Image-2.1-W4A4-int4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ModelsLab/Qwen-Image-2.1-W4A4-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("ModelsLab/Qwen-Image-2.1-W4A4-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
File size: 502 Bytes
117b828 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"_class_name": "QwenImage21Transformer2DModel",
"_diffusers_version": "0.41.0.dev0",
"_name_or_path": "/workspace/hf/hub/models--Qwen--Qwen-Image-2.1/snapshots/790c92633540aa0cb11d9abf19eb46d861714758/transformer",
"attention_head_dim": 128,
"axes_dims_rope": [
16,
56,
56
],
"causal_condition": true,
"context_in_dim": 4096,
"eps": 1e-06,
"in_channels": 64,
"mlp_ratio": 3,
"num_attention_heads": 32,
"num_layers": 32,
"out_channels": 64,
"patch_size": 1
}
|