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--- |
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language: |
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- en |
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library_name: transformers |
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quantized_by: mradermacher |
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--- |
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## About |
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weighted/imatrix quants https://huggingface.co/mlabonne/Beyonder-4x7B-v2 |
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<!-- provided-files --> |
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static quants are available at https://huggingface.co/mradermacher/Beyonder-4x7B-v2-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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READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for |
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more details, including on how to concatenate multi-part files. |
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## Provided Quants |
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(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) |
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| Link | Type | Size/GB | Notes | |
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|:-----|:-----|--------:|:------| |
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| [GGUF](https://huggingface.co/mradermacher/Beyonder-4x7B-v2-i1-GGUF/resolve/main/Beyonder-4x7B-v2.i1-IQ1_S.gguf) | i1-IQ1_S | 5.3 | for the desperate | |
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| [GGUF](https://huggingface.co/mradermacher/Beyonder-4x7B-v2-i1-GGUF/resolve/main/Beyonder-4x7B-v2.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 6.7 | | |
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| [GGUF](https://huggingface.co/mradermacher/Beyonder-4x7B-v2-i1-GGUF/resolve/main/Beyonder-4x7B-v2.i1-IQ2_XS.gguf) | i1-IQ2_XS | 7.4 | | |
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| [GGUF](https://huggingface.co/mradermacher/Beyonder-4x7B-v2-i1-GGUF/resolve/main/Beyonder-4x7B-v2.i1-IQ2_S.gguf) | i1-IQ2_S | 7.6 | | |
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| [GGUF](https://huggingface.co/mradermacher/Beyonder-4x7B-v2-i1-GGUF/resolve/main/Beyonder-4x7B-v2.i1-IQ2_M.gguf) | i1-IQ2_M | 8.3 | | |
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| [GGUF](https://huggingface.co/mradermacher/Beyonder-4x7B-v2-i1-GGUF/resolve/main/Beyonder-4x7B-v2.i1-Q2_K.gguf) | i1-Q2_K | 9.1 | IQ3_XXS probably better | |
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| [GGUF](https://huggingface.co/mradermacher/Beyonder-4x7B-v2-i1-GGUF/resolve/main/Beyonder-4x7B-v2.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 9.6 | lower quality | |
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| [GGUF](https://huggingface.co/mradermacher/Beyonder-4x7B-v2-i1-GGUF/resolve/main/Beyonder-4x7B-v2.i1-IQ3_XS.gguf) | i1-IQ3_XS | 10.1 | | |
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| [GGUF](https://huggingface.co/mradermacher/Beyonder-4x7B-v2-i1-GGUF/resolve/main/Beyonder-4x7B-v2.i1-Q3_K_S.gguf) | i1-Q3_K_S | 10.7 | IQ3_XS probably better | |
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| [GGUF](https://huggingface.co/mradermacher/Beyonder-4x7B-v2-i1-GGUF/resolve/main/Beyonder-4x7B-v2.i1-IQ3_S.gguf) | i1-IQ3_S | 10.7 | beats Q3_K* | |
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| [GGUF](https://huggingface.co/mradermacher/Beyonder-4x7B-v2-i1-GGUF/resolve/main/Beyonder-4x7B-v2.i1-IQ3_M.gguf) | i1-IQ3_M | 10.9 | | |
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| [GGUF](https://huggingface.co/mradermacher/Beyonder-4x7B-v2-i1-GGUF/resolve/main/Beyonder-4x7B-v2.i1-Q3_K_M.gguf) | i1-Q3_K_M | 11.8 | IQ3_S probably better | |
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| [GGUF](https://huggingface.co/mradermacher/Beyonder-4x7B-v2-i1-GGUF/resolve/main/Beyonder-4x7B-v2.i1-Q3_K_L.gguf) | i1-Q3_K_L | 12.8 | IQ3_M probably better | |
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| [GGUF](https://huggingface.co/mradermacher/Beyonder-4x7B-v2-i1-GGUF/resolve/main/Beyonder-4x7B-v2.i1-Q4_K_S.gguf) | i1-Q4_K_S | 14.0 | optimal size/speed/quality | |
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| [GGUF](https://huggingface.co/mradermacher/Beyonder-4x7B-v2-i1-GGUF/resolve/main/Beyonder-4x7B-v2.i1-Q4_K_M.gguf) | i1-Q4_K_M | 14.9 | fast, recommended | |
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| [GGUF](https://huggingface.co/mradermacher/Beyonder-4x7B-v2-i1-GGUF/resolve/main/Beyonder-4x7B-v2.i1-Q5_K_S.gguf) | i1-Q5_K_S | 16.9 | | |
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| [GGUF](https://huggingface.co/mradermacher/Beyonder-4x7B-v2-i1-GGUF/resolve/main/Beyonder-4x7B-v2.i1-Q5_K_M.gguf) | i1-Q5_K_M | 17.4 | | |
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| [GGUF](https://huggingface.co/mradermacher/Beyonder-4x7B-v2-i1-GGUF/resolve/main/Beyonder-4x7B-v2.i1-Q6_K.gguf) | i1-Q6_K | 20.1 | practically like static Q6_K | |
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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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And here are Artefact2's thoughts on the matter: |
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https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 |
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## FAQ / Model Request |
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See https://huggingface.co/mradermacher/model_requests for some answers to |
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questions you might have and/or if you want some other model quantized. |
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## Thanks |
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I thank my company, [nethype GmbH](https://www.nethype.de/), for letting |
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me use its servers and providing upgrades to my workstation to enable |
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this work in my free time. |
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