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  <!-- ### quantize_version: 2 -->
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  <!-- ### output_tensor_quantised: 1 -->
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  <!-- ### convert_type: hf -->
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  <!-- ### vocab_type: -->
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  <!-- ### tags: -->
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  static quants of https://huggingface.co/mistralai/Mixtral-8x22B-Instruct-v0.1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ base_model: mistralai/Mixtral-8x22B-Instruct-v0.1
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+ language:
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+ - en
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+ - es
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+ - it
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+ - de
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+ - fr
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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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+ ---
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+ ## About
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+
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  <!-- ### quantize_version: 2 -->
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  <!-- ### output_tensor_quantised: 1 -->
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  <!-- ### convert_type: hf -->
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  <!-- ### vocab_type: -->
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  <!-- ### tags: -->
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  static quants of https://huggingface.co/mistralai/Mixtral-8x22B-Instruct-v0.1
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+
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+ <!-- provided-files -->
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+ weighted/imatrix quants are available at https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-i1-GGUF
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+ ## Usage
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+
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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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+
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+ ## Provided Quants
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+
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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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+
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+ | Link | Type | Size/GB | Notes |
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+ |:-----|:-----|--------:|:------|
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+ | [PART 1](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q2_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q2_K.gguf.part2of2) | Q2_K | 52.2 | |
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+ | [PART 1](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.IQ3_XS.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.IQ3_XS.gguf.part2of2) | IQ3_XS | 58.3 | |
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+ | [PART 1](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.IQ3_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.IQ3_S.gguf.part2of2) | IQ3_S | 61.6 | beats Q3_K* |
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+ | [PART 1](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q3_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q3_K_S.gguf.part2of2) | Q3_K_S | 61.6 | |
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+ | [PART 1](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.IQ3_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.IQ3_M.gguf.part2of2) | IQ3_M | 64.6 | |
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+ | [PART 1](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q3_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q3_K_M.gguf.part2of2) | Q3_K_M | 67.9 | lower quality |
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+ | [PART 1](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q3_K_L.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q3_K_L.gguf.part2of2) | Q3_K_L | 72.7 | |
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+ | [PART 1](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.IQ4_XS.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.IQ4_XS.gguf.part2of2) | IQ4_XS | 76.5 | |
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+ | [PART 1](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q4_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q4_K_S.gguf.part2of2) | Q4_K_S | 80.6 | fast, recommended |
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+ | [PART 1](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q4_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q4_K_M.gguf.part2of2) | Q4_K_M | 85.7 | fast, recommended |
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+ | [PART 1](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q5_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q5_K_S.gguf.part2of2) | Q5_K_S | 97.1 | |
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+ | [PART 1](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q5_K_M.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q5_K_M.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q5_K_M.gguf.part3of3) | Q5_K_M | 100.1 | |
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+ | [PART 1](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q6_K.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q6_K.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q6_K.gguf.part3of3) | Q6_K | 115.6 | very good quality |
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+ | [PART 1](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q8_0.gguf.part1of4) [PART 2](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q8_0.gguf.part2of4) [PART 3](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q8_0.gguf.part3of4) [PART 4](https://huggingface.co/mradermacher/Mixtral-8x22B-Instruct-v0.1-GGUF/resolve/main/Mixtral-8x22B-Instruct-v0.1.Q8_0.gguf.part4of4) | Q8_0 | 149.5 | fast, best quality |
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+
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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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+
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+ ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
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+
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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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+
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+ ## FAQ / Model Request
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+
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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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+
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+ ## Thanks
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+
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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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+
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+ <!-- end -->