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@@ -49,7 +49,7 @@ static quants of https://huggingface.co/aifeifei798/DarkIdol-Llama-3.1-8B-Instru
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  ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored-GGUF).***
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- weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
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  ## Usage
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  If you are unsure how to use GGUF files, refer to one of [TheBloke's
@@ -63,7 +63,17 @@ more details, including on how to concatenate multi-part files.
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  | Link | Type | Size/GB | Notes |
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  |:-----|:-----|--------:|:------|
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  | [GGUF](https://huggingface.co/mradermacher/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored-GGUF/resolve/main/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored.Q2_K.gguf) | Q2_K | 3.3 | |
 
 
 
 
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  | [GGUF](https://huggingface.co/mradermacher/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored-GGUF/resolve/main/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored.Q4_K_S.gguf) | Q4_K_S | 4.8 | fast, recommended |
 
 
 
 
 
 
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  Here is a handy graph by ikawrakow comparing some lower-quality quant
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  types (lower is better):
 
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  ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored-GGUF).***
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+ weighted/imatrix quants are available at https://huggingface.co/mradermacher/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored-i1-GGUF
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  ## Usage
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  If you are unsure how to use GGUF files, refer to one of [TheBloke's
 
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  | Link | Type | Size/GB | Notes |
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  |:-----|:-----|--------:|:------|
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  | [GGUF](https://huggingface.co/mradermacher/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored-GGUF/resolve/main/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored.Q2_K.gguf) | Q2_K | 3.3 | |
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+ | [GGUF](https://huggingface.co/mradermacher/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored-GGUF/resolve/main/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored.Q3_K_S.gguf) | Q3_K_S | 3.8 | |
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+ | [GGUF](https://huggingface.co/mradermacher/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored-GGUF/resolve/main/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored.Q3_K_M.gguf) | Q3_K_M | 4.1 | lower quality |
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+ | [GGUF](https://huggingface.co/mradermacher/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored-GGUF/resolve/main/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored.Q3_K_L.gguf) | Q3_K_L | 4.4 | |
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+ | [GGUF](https://huggingface.co/mradermacher/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored-GGUF/resolve/main/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored.IQ4_XS.gguf) | IQ4_XS | 4.6 | |
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  | [GGUF](https://huggingface.co/mradermacher/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored-GGUF/resolve/main/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored.Q4_K_S.gguf) | Q4_K_S | 4.8 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored-GGUF/resolve/main/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored.Q4_K_M.gguf) | Q4_K_M | 5.0 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored-GGUF/resolve/main/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored.Q5_K_S.gguf) | Q5_K_S | 5.7 | |
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+ | [GGUF](https://huggingface.co/mradermacher/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored-GGUF/resolve/main/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored.Q5_K_M.gguf) | Q5_K_M | 5.8 | |
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+ | [GGUF](https://huggingface.co/mradermacher/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored-GGUF/resolve/main/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored.Q6_K.gguf) | Q6_K | 6.7 | very good quality |
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+ | [GGUF](https://huggingface.co/mradermacher/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored-GGUF/resolve/main/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored.Q8_0.gguf) | Q8_0 | 8.6 | fast, best quality |
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+ | [GGUF](https://huggingface.co/mradermacher/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored-GGUF/resolve/main/DarkIdol-Llama-3.1-8B-Instruct-1.3-Uncensored.f16.gguf) | f16 | 16.2 | 16 bpw, overkill |
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  Here is a handy graph by ikawrakow comparing some lower-quality quant
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  types (lower is better):