Instructions to use vladmandic/Krea-2-Base-sdnq-hadamard-uint4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vladmandic/Krea-2-Base-sdnq-hadamard-uint4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("vladmandic/Krea-2-Base-sdnq-hadamard-uint4", 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
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| "dequantize_fp32": false, | |
| "dynamic_loss_threshold": -1, | |
| "group_size": 0, | |
| "hadamard_group_size": 256, | |
| "is_integer": true, | |
| "is_training": false, | |
| "modules_dtype_dict": { | |
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| }, | |
| "modules_quant_config": {}, | |
| "modules_to_not_convert": [ | |
| ".txt_out", | |
| ".time_embed", | |
| ".vid_out", | |
| ".vid_in", | |
| ".txt_in", | |
| ".img_in", | |
| ".emb_out", | |
| "first", | |
| ".norm_out", | |
| "multi_modal_projector", | |
| ".img_out", | |
| "tproj", | |
| ".t_embedder", | |
| ".emb_in", | |
| ".final_layer", | |
| "last", | |
| "patch_embedding", | |
| ".proj_out", | |
| "time_text_embed", | |
| "tmlp", | |
| "patch_embed", | |
| ".x_embedder", | |
| "patch_emb", | |
| "wte", | |
| ".y_embedder", | |
| ".condition_embedder", | |
| ".context_embedder", | |
| "projector", | |
| "lm_head" | |
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| "modules_to_not_use_matmul": [], | |
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| "quant_conv": false, | |
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| "weights_dtype": "uint4" | |
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