auto-patch README.md
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README.md
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<!-- ### quantize_version: 1 -->
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<!-- ### output_tensor_quantised: 1 -->
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<!-- ### convert_type: -->
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<!-- ### vocab_type: -->
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weighted/imatrix quants of https://huggingface.co/Aratako/Mixtral-8x7B-Instruct-v0.1-upscaled
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---
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base_model:
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- mistralai/Mixtral-8x7B-Instruct-v0.1
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exported_from: Aratako/Mixtral-8x7B-Instruct-v0.1-upscaled
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language:
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- en
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library_name: transformers
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license: apache-2.0
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quantized_by: mradermacher
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tags:
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- mergekit
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- merge
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---
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## About
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<!-- ### quantize_version: 1 -->
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<!-- ### output_tensor_quantised: 1 -->
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<!-- ### convert_type: -->
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<!-- ### vocab_type: -->
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weighted/imatrix quants of https://huggingface.co/Aratako/Mixtral-8x7B-Instruct-v0.1-upscaled
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<!-- provided-files -->
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static quants are available at https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-upscaled-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/Mixtral-8x7B-Instruct-v0.1-upscaled-i1-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-upscaled.i1-IQ2_M.gguf) | i1-IQ2_M | 27.1 | |
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| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-upscaled-i1-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-upscaled.i1-Q2_K.gguf) | i1-Q2_K | 30.3 | IQ3_XXS probably better |
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| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-upscaled-i1-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-upscaled.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 31.9 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-upscaled-i1-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-upscaled.i1-IQ3_XS.gguf) | i1-IQ3_XS | 33.7 | |
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| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-upscaled-i1-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-upscaled.i1-Q3_K_S.gguf) | i1-Q3_K_S | 35.7 | IQ3_XS probably better |
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| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-upscaled-i1-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-upscaled.i1-Q3_K_M.gguf) | i1-Q3_K_M | 39.4 | IQ3_S probably better |
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| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-upscaled-i1-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-upscaled.i1-Q3_K_L.gguf) | i1-Q3_K_L | 42.3 | IQ3_M probably better |
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| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-upscaled-i1-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-upscaled.i1-IQ4_XS.gguf) | i1-IQ4_XS | 43.9 | |
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| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-upscaled-i1-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-upscaled.i1-Q4_0.gguf) | i1-Q4_0 | 46.4 | fast, low quality |
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| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-upscaled-i1-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-upscaled.i1-Q4_K_S.gguf) | i1-Q4_K_S | 46.8 | optimal size/speed/quality |
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| [PART 1](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-upscaled-i1-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-upscaled.i1-Q4_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-upscaled-i1-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-upscaled.i1-Q4_K_M.gguf.part2of2) | i1-Q4_K_M | 49.7 | fast, recommended |
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| [PART 1](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-upscaled-i1-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-upscaled.i1-Q5_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-upscaled-i1-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-upscaled.i1-Q5_K_S.gguf.part2of2) | i1-Q5_K_S | 56.4 | |
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| [PART 1](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-upscaled-i1-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-upscaled.i1-Q5_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-upscaled-i1-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-upscaled.i1-Q5_K_M.gguf.part2of2) | i1-Q5_K_M | 58.1 | |
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| [PART 1](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-upscaled-i1-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-upscaled.i1-Q6_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Mixtral-8x7B-Instruct-v0.1-upscaled-i1-GGUF/resolve/main/Mixtral-8x7B-Instruct-v0.1-upscaled.i1-Q6_K.gguf.part2of2) | i1-Q6_K | 67.1 | 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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## 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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<!-- end -->
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