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codegemma-7b-GGUF

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@@ -22,7 +22,7 @@ quantized_by: mradermacher
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  static quants of https://huggingface.co/google/codegemma-7b
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  <!-- provided-files -->
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- weighted/imatrix quants are available at https://huggingface.co/mradermacher/codegemma-7b-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
@@ -35,19 +35,19 @@ 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/codegemma-7b-GGUF/resolve/main/codegemma-7b.Q4_0_4_4.gguf) | Q4_0_4_4 | 5.1 | fast on arm, low quality |
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- | [PART 1](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/CodeGemma-7b.Q2_K.gguf) [PART 2](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/codegemma-7b.Q2_K.gguf) | Q2_K | 7.1 | |
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- | [PART 1](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/CodeGemma-7b.Q3_K_S.gguf) [PART 2](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/codegemma-7b.Q3_K_S.gguf) | Q3_K_S | 8.1 | |
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- | [PART 1](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/CodeGemma-7b.Q3_K_M.gguf) [PART 2](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/codegemma-7b.Q3_K_M.gguf) | Q3_K_M | 8.8 | lower quality |
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- | [PART 1](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/CodeGemma-7b.Q3_K_L.gguf) [PART 2](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/codegemma-7b.Q3_K_L.gguf) | Q3_K_L | 9.5 | |
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- | [PART 1](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/CodeGemma-7b.IQ4_XS.gguf) [PART 2](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/codegemma-7b.IQ4_XS.gguf) | IQ4_XS | 9.7 | |
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- | [PART 1](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/CodeGemma-7b.Q4_K_S.gguf) [PART 2](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/codegemma-7b.Q4_K_S.gguf) | Q4_K_S | 10.2 | fast, recommended |
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- | [PART 1](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/CodeGemma-7b.Q4_K_M.gguf) [PART 2](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/codegemma-7b.Q4_K_M.gguf) | Q4_K_M | 10.8 | fast, recommended |
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- | [PART 1](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/CodeGemma-7b.Q5_K_S.gguf) [PART 2](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/codegemma-7b.Q5_K_S.gguf) | Q5_K_S | 12.1 | |
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- | [PART 1](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/CodeGemma-7b.Q5_K_M.gguf) [PART 2](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/codegemma-7b.Q5_K_M.gguf) | Q5_K_M | 12.4 | |
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- | [PART 1](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/CodeGemma-7b.Q6_K.gguf) [PART 2](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/codegemma-7b.Q6_K.gguf) | Q6_K | 14.1 | very good quality |
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- | [PART 1](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/CodeGemma-7b.Q8_0.gguf) [PART 2](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/codegemma-7b.Q8_0.gguf) | Q8_0 | 18.3 | fast, best quality |
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- | [PART 1](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/CodeGemma-7b.f16.gguf) [PART 2](https://huggingface.co/mradermacher/codegemma-7b-GGUF/resolve/main/codegemma-7b.f16.gguf) | f16 | 34.3 | 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):
 
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  static quants of https://huggingface.co/google/codegemma-7b
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  <!-- provided-files -->
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+ weighted/imatrix quants are available at https://huggingface.co/mradermacher/CodeGemma-7b-i1-GGUF
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  ## Usage
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28
  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/CodeGemma-7b-GGUF/resolve/main/codegemma-7b.Q4_0_4_4.gguf) | Q4_0_4_4 | 5.1 | fast on arm, low quality |
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+ | [PART 1](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/CodeGemma-7b.Q2_K.gguf) [PART 2](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/codegemma-7b.Q2_K.gguf) | Q2_K | 7.1 | |
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+ | [PART 1](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/CodeGemma-7b.Q3_K_S.gguf) [PART 2](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/codegemma-7b.Q3_K_S.gguf) | Q3_K_S | 8.1 | |
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+ | [PART 1](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/CodeGemma-7b.Q3_K_M.gguf) [PART 2](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/codegemma-7b.Q3_K_M.gguf) | Q3_K_M | 8.8 | lower quality |
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+ | [PART 1](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/CodeGemma-7b.Q3_K_L.gguf) [PART 2](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/codegemma-7b.Q3_K_L.gguf) | Q3_K_L | 9.5 | |
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+ | [PART 1](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/CodeGemma-7b.IQ4_XS.gguf) [PART 2](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/codegemma-7b.IQ4_XS.gguf) | IQ4_XS | 9.7 | |
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+ | [PART 1](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/CodeGemma-7b.Q4_K_S.gguf) [PART 2](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/codegemma-7b.Q4_K_S.gguf) | Q4_K_S | 10.2 | fast, recommended |
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+ | [PART 1](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/CodeGemma-7b.Q4_K_M.gguf) [PART 2](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/codegemma-7b.Q4_K_M.gguf) | Q4_K_M | 10.8 | fast, recommended |
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+ | [PART 1](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/CodeGemma-7b.Q5_K_S.gguf) [PART 2](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/codegemma-7b.Q5_K_S.gguf) | Q5_K_S | 12.1 | |
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+ | [PART 1](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/CodeGemma-7b.Q5_K_M.gguf) [PART 2](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/codegemma-7b.Q5_K_M.gguf) | Q5_K_M | 12.4 | |
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+ | [PART 1](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/CodeGemma-7b.Q6_K.gguf) [PART 2](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/codegemma-7b.Q6_K.gguf) | Q6_K | 14.1 | very good quality |
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+ | [PART 1](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/CodeGemma-7b.Q8_0.gguf) [PART 2](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/codegemma-7b.Q8_0.gguf) | Q8_0 | 18.3 | fast, best quality |
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+ | [PART 1](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/CodeGemma-7b.f16.gguf) [PART 2](https://huggingface.co/mradermacher/CodeGemma-7b-GGUF/resolve/main/codegemma-7b.f16.gguf) | f16 | 34.3 | 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):