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f2_from_diffusers.py and then selectively quantized (hopefully) all binary tensors using sd.cpp.sd-cli -M convert -m bonsai-image-unpacked.safetensors -o bonsai_image_4b-q1_0.gguf --tensor-type-rules "^single_blocks.[0-9]+.linear1.weight=q1_0,^single_blocks.[0-9]+.linear2.weight=q1_0,^double_blocks.[0-9]+.img_attn.qkv.weight=q1_0,^double_blocks.[0-9]+.img_attn.proj.weight=q1_0,^double_blocks.[0-9]+.txt_attn.qkv.weight=q1_0,^double_blocks.[0-9]+.txt_attn.proj.weight=q1_0,^double_blocks.[0-9]+.img_mlp.[0-9].weight=q1_0,^double_blocks.[0-9]+.txt_mlp.[0-9].weight=q1_0"sd-cli -M convert -m models/bonsai_image_4b-q1_0.gguf -o models/bonsai_image_4b-mod_q8_0-q1_0.gguf --tensor-type-rules "^double_stream_modulation_img.lin.weight=q8_0,^double_stream_modulation_txt.lin.weight=q8_0"| base (q1_0+bf16) | mod_q8_0 (q1_0+q8_0+bf16) |
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sd-cli --diffusion-model models/bonsai_image_4b-q1_0.gguf --llm models/Qwen3-4B-UD-IQ3_XXS.gguf --steps 6 --vae models/flux2/full_encoder_small_decoder.safetensors --offload-to-cpu --cfg-scale 1.0 --fa -p "a lovely cat" -H 1024 -W 1024 --vae-tiling --vae-tile-size 64 --sampling-method dpm++2s_a -o bonsai-q1_0_base.png