Instructions to use codeShare/Klein9B-DarkBeast-SDNQ-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codeShare/Klein9B-DarkBeast-SDNQ-4bit 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/Klein9B-DarkBeast-SDNQ-4bit", 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
Delete transformer
Browse files
transformer/config.json
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{
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"_class_name": "Flux2Transformer2DModel",
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"_diffusers_version": "0.37.1",
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"_name_or_path": "/content/transformer_flux2klein",
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"attention_head_dim": 128,
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"axes_dims_rope": [
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32,
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32,
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32,
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32
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],
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"eps": 1e-06,
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"guidance_embeds": false,
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"in_channels": 128,
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"joint_attention_dim": 12288,
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"mlp_ratio": 3.0,
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"num_attention_heads": 32,
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"num_layers": 8,
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"num_single_layers": 24,
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"out_channels": null,
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"patch_size": 1,
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"quantization_config": {
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"add_skip_keys": true,
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"dequantize_fp32": true,
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"dynamic_loss_threshold": 0.01,
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"group_size": 0,
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"is_integer": true,
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"is_training": false,
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"modules_dtype_dict": {
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"int8": [
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"proj_out",
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"norm_out"
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]
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},
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"modules_quant_config": {},
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"modules_to_not_convert": [
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"double_stream_modulation_txt",
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"embedding_projection",
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"time_guidance_embed",
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"norm_out",
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"double_stream_modulation_img",
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"single_stream_modulation",
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"x_embedder",
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"norm_k",
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"visual",
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"correction_coefs",
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"proj_out",
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"lm_head",
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"norm_added_k",
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".proj_out",
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"prediction_coefs",
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"norm_added_q",
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"norm_q",
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"context_embedder"
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],
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"non_blocking": false,
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"quant_conv": false,
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"quant_embedding": false,
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"quant_method": "sdnq",
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"quantization_device": "cuda",
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"quantized_matmul_dtype": null,
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"return_device": "cpu",
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"sdnq_version": "0.1.8",
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"svd_rank": 32,
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"svd_steps": 16,
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"use_dynamic_quantization": true,
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"use_grad_ckpt": true,
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"use_quantized_matmul": false,
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"use_quantized_matmul_conv": false,
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"use_static_quantization": true,
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"use_stochastic_rounding": false,
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"use_svd": true,
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"weights_dtype": "uint4"
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},
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"rope_theta": 2000,
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"timestep_guidance_channels": 256
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}
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transformer/diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:fc8c699a5e32ce607d349637a65a179e47e0221943af29104d21913df6f71e0b
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size 9078610304
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