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@@ -24,7 +24,7 @@ static quants of https://huggingface.co/ZejunLi/AdaVaR-3B
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  ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#AdaVaR-3B-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
@@ -38,7 +38,19 @@ 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/AdaVaR-3B-GGUF/resolve/main/AdaVaR-3B.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 0.9 | multi-modal supplement |
 
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  | [GGUF](https://huggingface.co/mradermacher/AdaVaR-3B-GGUF/resolve/main/AdaVaR-3B.mmproj-f16.gguf) | mmproj-f16 | 1.4 | multi-modal supplement |
 
 
 
 
 
 
 
 
 
 
 
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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#AdaVaR-3B-GGUF).***
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+ weighted/imatrix quants are available at https://huggingface.co/mradermacher/AdaVaR-3B-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/AdaVaR-3B-GGUF/resolve/main/AdaVaR-3B.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 0.9 | multi-modal supplement |
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+ | [GGUF](https://huggingface.co/mradermacher/AdaVaR-3B-GGUF/resolve/main/AdaVaR-3B.Q2_K.gguf) | Q2_K | 1.4 | |
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  | [GGUF](https://huggingface.co/mradermacher/AdaVaR-3B-GGUF/resolve/main/AdaVaR-3B.mmproj-f16.gguf) | mmproj-f16 | 1.4 | multi-modal supplement |
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+ | [GGUF](https://huggingface.co/mradermacher/AdaVaR-3B-GGUF/resolve/main/AdaVaR-3B.Q3_K_S.gguf) | Q3_K_S | 1.6 | |
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+ | [GGUF](https://huggingface.co/mradermacher/AdaVaR-3B-GGUF/resolve/main/AdaVaR-3B.Q3_K_M.gguf) | Q3_K_M | 1.7 | lower quality |
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+ | [GGUF](https://huggingface.co/mradermacher/AdaVaR-3B-GGUF/resolve/main/AdaVaR-3B.Q3_K_L.gguf) | Q3_K_L | 1.8 | |
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+ | [GGUF](https://huggingface.co/mradermacher/AdaVaR-3B-GGUF/resolve/main/AdaVaR-3B.IQ4_XS.gguf) | IQ4_XS | 1.9 | |
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+ | [GGUF](https://huggingface.co/mradermacher/AdaVaR-3B-GGUF/resolve/main/AdaVaR-3B.Q4_K_S.gguf) | Q4_K_S | 1.9 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/AdaVaR-3B-GGUF/resolve/main/AdaVaR-3B.Q4_K_M.gguf) | Q4_K_M | 2.0 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/AdaVaR-3B-GGUF/resolve/main/AdaVaR-3B.Q5_K_S.gguf) | Q5_K_S | 2.3 | |
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+ | [GGUF](https://huggingface.co/mradermacher/AdaVaR-3B-GGUF/resolve/main/AdaVaR-3B.Q5_K_M.gguf) | Q5_K_M | 2.3 | |
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+ | [GGUF](https://huggingface.co/mradermacher/AdaVaR-3B-GGUF/resolve/main/AdaVaR-3B.Q6_K.gguf) | Q6_K | 2.6 | very good quality |
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+ | [GGUF](https://huggingface.co/mradermacher/AdaVaR-3B-GGUF/resolve/main/AdaVaR-3B.Q8_0.gguf) | Q8_0 | 3.4 | fast, best quality |
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+ | [GGUF](https://huggingface.co/mradermacher/AdaVaR-3B-GGUF/resolve/main/AdaVaR-3B.f16.gguf) | f16 | 6.3 | 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):