Instructions to use codeShare/unstableRevolution_SDNQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codeShare/unstableRevolution_SDNQ with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("codeShare/unstableRevolution_SDNQ", 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
| { | |
| "_class_name": "Flux2Transformer2DModel", | |
| "_diffusers_version": "0.38.0.dev0", | |
| "_name_or_path": "codeShare/FLUX.2-klein-AIO-SDNQ-4bit-dynamic", | |
| "attention_head_dim": 128, | |
| "axes_dims_rope": [ | |
| 32, | |
| 32, | |
| 32, | |
| 32 | |
| ], | |
| "eps": 1e-06, | |
| "guidance_embeds": false, | |
| "in_channels": 128, | |
| "joint_attention_dim": 7680, | |
| "mlp_ratio": 3.0, | |
| "num_attention_heads": 24, | |
| "num_layers": 5, | |
| "num_single_layers": 20, | |
| "out_channels": null, | |
| "patch_size": 1, | |
| "quantization_config": { | |
| "add_skip_keys": false, | |
| "dequantize_fp32": true, | |
| "dynamic_loss_threshold": 0.01, | |
| "group_size": 0, | |
| "is_integer": true, | |
| "is_training": false, | |
| "modules_dtype_dict": { | |
| "int5": [ | |
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| ] | |
| }, | |
| "modules_quant_config": {}, | |
| "modules_to_not_convert": [ | |
| "time_guidance_embed", | |
| "norm_out", | |
| "context_embedder", | |
| "double_stream_modulation_txt", | |
| "x_embedder", | |
| "double_stream_modulation_img", | |
| ".proj_out", | |
| "single_stream_modulation" | |
| ], | |
| "non_blocking": false, | |
| "quant_conv": false, | |
| "quant_embedding": false, | |
| "quant_method": "sdnq", | |
| "quantization_device": null, | |
| "quantized_matmul_dtype": null, | |
| "return_device": null, | |
| "sdnq_version": "0.1.7", | |
| "svd_rank": 32, | |
| "svd_steps": 8, | |
| "use_dynamic_quantization": true, | |
| "use_grad_ckpt": true, | |
| "use_quantized_matmul": false, | |
| "use_quantized_matmul_conv": false, | |
| "use_static_quantization": true, | |
| "use_stochastic_rounding": false, | |
| "use_svd": false, | |
| "weights_dtype": "uint4" | |
| }, | |
| "rope_theta": 2000, | |
| "timestep_guidance_channels": 256 | |
| } | |