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Fix links in README

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  1. README.md +7 -7
README.md CHANGED
@@ -25,16 +25,16 @@ Only the second layers of both MLPs in each MMDiT block of SD3.5 Large models ha
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  - [sd3.5_large-q2_k_4_0.gguf](https://huggingface.co/stduhpf/SD3.5-Large-GGUF-mixed-sdcpp/blob/main/sd3.5_large-q2_k_4_0.gguf): Smallest quantization yet. Use this if you can't afford anything bigger
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  - [sd3.5_large-q3_k_4_0.gguf](https://huggingface.co/stduhpf/SD3.5-Large-GGUF-mixed-sdcpp/blob/main/sd3.5_large-q3_k_4_0.gguf): Degraded, but usable at high step count.
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  - [sd3.5_large-q4_k_4_0.gguf](https://huggingface.co/stduhpf/SD3.5-Large-GGUF-mixed-sdcpp/blob/main/sd3.5_large-q4_k_4_0.gguf): Exacty same size as q4_0, but with slightly less degradation. Recommended
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- - [sd3.5_large-q4_k_4_1.gguf](https://huggingface.co/stduhpf/SD3.5-Large-Turbo-GGUF-mixed-sdcpp/blob/main/sd3.5_large-q4_k_4_1.gguf): Smaller than q4_1, and with comparable degradation. Recommended
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- - [sd3.5_large-q4_k_5_0.gguf](https://huggingface.co/stduhpf/SD3.5-Large-Turbo-GGUF-mixed-sdcpp/blob/main/sd3.5_large-q4_k_5_0.gguf): Smaller than q5_0, and with comparable degradation. Very close to the original f16 already. Recommended
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  ### Legacy types:
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- - [sd3.5_large-q4_0.gguf](https://huggingface.co/stduhpf/SD3.5-Large-Turbo-GGUF-mixed-sdcpp/blob/main/legacy/sd3.5_large-q4_0.gguf): Same size as q4_k_4_0, Not recommended (use q4_k_4_0 instead)
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- - [sd3.5_large-q4_1.gguf](https://huggingface.co/stduhpf/SD3.5-Large-Turbo-GGUF-mixed-sdcpp/blob/main/legacy/sd3.5_large-q4_1.gguf): Not recommended (q4_k_4_1 is better and smaller)
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- - [sd3.5_large-q5_0.gguf](https://huggingface.co/stduhpf/SD3.5-Large-Turbo-GGUF-mixed-sdcpp/blob/main/legacy/sd3.5_large-q5_0.gguf): Barely better and bigger than q4_k_5_0
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- - [sd3.5_large-q5_1.gguf](https://huggingface.co/stduhpf/SD3.5-Large-Turbo-GGUF-mixed-sdcpp/blob/main/legacy/sd3.5_large-q5_1.gguf): Better and bigger than q5_0
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- - [sd3.5_large-q8_0.gguf](https://huggingface.co/stduhpf/SD3.5-Large-Turbo-GGUF-mixed-sdcpp/blob/main/legacy/sd3.5_large-q8_0.gguf): Basically indistinguishable from the original f16, but much smaller. Recommended for best quality
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  ## Outputs:
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  - [sd3.5_large-q2_k_4_0.gguf](https://huggingface.co/stduhpf/SD3.5-Large-GGUF-mixed-sdcpp/blob/main/sd3.5_large-q2_k_4_0.gguf): Smallest quantization yet. Use this if you can't afford anything bigger
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  - [sd3.5_large-q3_k_4_0.gguf](https://huggingface.co/stduhpf/SD3.5-Large-GGUF-mixed-sdcpp/blob/main/sd3.5_large-q3_k_4_0.gguf): Degraded, but usable at high step count.
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  - [sd3.5_large-q4_k_4_0.gguf](https://huggingface.co/stduhpf/SD3.5-Large-GGUF-mixed-sdcpp/blob/main/sd3.5_large-q4_k_4_0.gguf): Exacty same size as q4_0, but with slightly less degradation. Recommended
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+ - [sd3.5_large-q4_k_4_1.gguf](https://huggingface.co/stduhpf/SD3.5-Large-GGUF-mixed-sdcpp/blob/main/sd3.5_large-q4_k_4_1.gguf): Smaller than q4_1, and with comparable degradation. Recommended
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+ - [sd3.5_large-q4_k_5_0.gguf](https://huggingface.co/stduhpf/SD3.5-Large-GGUF-mixed-sdcpp/blob/main/sd3.5_large-q4_k_5_0.gguf): Smaller than q5_0, and with comparable degradation. Very close to the original f16 already. Recommended
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  ### Legacy types:
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+ - [sd3.5_large-q4_0.gguf](https://huggingface.co/stduhpf/SD3.5-Large-GGUF-mixed-sdcpp/blob/main/legacy/sd3.5_large-q4_0.gguf): Same size as q4_k_4_0, Not recommended (use q4_k_4_0 instead)
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+ - [sd3.5_large-q4_1.gguf](https://huggingface.co/stduhpf/SD3.5-Large-GGUF-mixed-sdcpp/blob/main/legacy/sd3.5_large-q4_1.gguf): Not recommended (q4_k_4_1 is better and smaller)
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+ - [sd3.5_large-q5_0.gguf](https://huggingface.co/stduhpf/SD3.5-Large-GGUF-mixed-sdcpp/blob/main/legacy/sd3.5_large-q5_0.gguf): Barely better and bigger than q4_k_5_0
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+ - [sd3.5_large-q5_1.gguf](https://huggingface.co/stduhpf/SD3.5-Large-GGUF-mixed-sdcpp/blob/main/legacy/sd3.5_large-q5_1.gguf): Better and bigger than q5_0
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+ - [sd3.5_large-q8_0.gguf](https://huggingface.co/stduhpf/SD3.5-Large-GGUF-mixed-sdcpp/blob/main/legacy/sd3.5_large-q8_0.gguf): Basically indistinguishable from the original f16, but much smaller. Recommended for best quality
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  ## Outputs:
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