Text-to-Image
Diffusers
Safetensors
MageFlowPipeline
ajh
mage-flow
mage-flow-nvfp4-ajh
nvfp4
blackwell
qwen3-vl
quantization
Instructions to use ajh-code/Mage-Flow-NVFP4-AJH with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ajh-code/Mage-Flow-NVFP4-AJH with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ajh-code/Mage-Flow-NVFP4-AJH", torch_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
| { | |
| "_class_name": "MageFlow", | |
| "apply_text_rotary_emb": false, | |
| "axes_dim": [ | |
| 16, | |
| 56, | |
| 56 | |
| ], | |
| "checkpoint": false, | |
| "context_in_dim": 2560, | |
| "depth": 12, | |
| "depth_single_blocks": 0, | |
| "double_block_type": "double_stream", | |
| "guidance_embed": false, | |
| "hidden_size": 3072, | |
| "in_channels": 128, | |
| "max_sequence_length": 2048, | |
| "mlp_ratio": 4.0, | |
| "num_heads": 24, | |
| "out_channels": 128, | |
| "packing": true, | |
| "param_dtype": "bfloat16", | |
| "patch_size": 1, | |
| "qkv_bias": true, | |
| "quantization_config": { | |
| "backend": "native_sm120", | |
| "compute_dtype": "bfloat16", | |
| "format": "e2m1_block16_ue4m3", | |
| "quant_algo": "NVFP4", | |
| "quant_method": "mage_flow_nvfp4", | |
| "target_count": 48, | |
| "targets": [ | |
| "transformer_blocks.0.img_mlp.net.0.proj", | |
| "transformer_blocks.0.img_mlp.net.2", | |
| "transformer_blocks.0.txt_mlp.net.0.proj", | |
| "transformer_blocks.0.txt_mlp.net.2", | |
| "transformer_blocks.1.img_mlp.net.0.proj", | |
| "transformer_blocks.1.img_mlp.net.2", | |
| "transformer_blocks.1.txt_mlp.net.0.proj", | |
| "transformer_blocks.1.txt_mlp.net.2", | |
| "transformer_blocks.2.img_mlp.net.0.proj", | |
| "transformer_blocks.2.img_mlp.net.2", | |
| "transformer_blocks.2.txt_mlp.net.0.proj", | |
| "transformer_blocks.2.txt_mlp.net.2", | |
| "transformer_blocks.3.img_mlp.net.0.proj", | |
| "transformer_blocks.3.img_mlp.net.2", | |
| "transformer_blocks.3.txt_mlp.net.0.proj", | |
| "transformer_blocks.3.txt_mlp.net.2", | |
| "transformer_blocks.4.img_mlp.net.0.proj", | |
| "transformer_blocks.4.img_mlp.net.2", | |
| "transformer_blocks.4.txt_mlp.net.0.proj", | |
| "transformer_blocks.4.txt_mlp.net.2", | |
| "transformer_blocks.5.img_mlp.net.0.proj", | |
| "transformer_blocks.5.img_mlp.net.2", | |
| "transformer_blocks.5.txt_mlp.net.0.proj", | |
| "transformer_blocks.5.txt_mlp.net.2", | |
| "transformer_blocks.6.img_mlp.net.0.proj", | |
| "transformer_blocks.6.img_mlp.net.2", | |
| "transformer_blocks.6.txt_mlp.net.0.proj", | |
| "transformer_blocks.6.txt_mlp.net.2", | |
| "transformer_blocks.7.img_mlp.net.0.proj", | |
| "transformer_blocks.7.img_mlp.net.2", | |
| "transformer_blocks.7.txt_mlp.net.0.proj", | |
| "transformer_blocks.7.txt_mlp.net.2", | |
| "transformer_blocks.8.img_mlp.net.0.proj", | |
| "transformer_blocks.8.img_mlp.net.2", | |
| "transformer_blocks.8.txt_mlp.net.0.proj", | |
| "transformer_blocks.8.txt_mlp.net.2", | |
| "transformer_blocks.9.img_mlp.net.0.proj", | |
| "transformer_blocks.9.img_mlp.net.2", | |
| "transformer_blocks.9.txt_mlp.net.0.proj", | |
| "transformer_blocks.9.txt_mlp.net.2", | |
| "transformer_blocks.10.img_mlp.net.0.proj", | |
| "transformer_blocks.10.img_mlp.net.2", | |
| "transformer_blocks.10.txt_mlp.net.0.proj", | |
| "transformer_blocks.10.txt_mlp.net.2", | |
| "transformer_blocks.11.img_mlp.net.0.proj", | |
| "transformer_blocks.11.img_mlp.net.2", | |
| "transformer_blocks.11.txt_mlp.net.0.proj", | |
| "transformer_blocks.11.txt_mlp.net.2" | |
| ] | |
| }, | |
| "rope_type": "msrope", | |
| "schedule_mode": "z-image", | |
| "static_shift": 6.0, | |
| "theta": 10000, | |
| "time_type": "qwen_proj", | |
| "txt_max_length": 2048, | |
| "use_time_shift": false, | |
| "vec_in_dim": 0, | |
| "vec_type": null | |
| } | |