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auto-patch README.md
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README.md
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static quants of https://huggingface.co/jondurbin/airoboros-l2-c70b-3.1.2
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---
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datasets:
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- jondurbin/airoboros-3.1
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language:
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- en
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library_name: transformers
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license: llama2
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quantized_by: mradermacher
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---
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## About
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static quants of https://huggingface.co/jondurbin/airoboros-l2-c70b-3.1.2
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<!-- provided-files -->
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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/airoboros-l2-c70b-3.1.2-GGUF/resolve/main/airoboros-l2-c70b-3.1.2.Q2_K.gguf) | Q2_K | 25.9 | |
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| [GGUF](https://huggingface.co/mradermacher/airoboros-l2-c70b-3.1.2-GGUF/resolve/main/airoboros-l2-c70b-3.1.2.Q3_K_S.gguf) | Q3_K_S | 30.3 | |
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| [GGUF](https://huggingface.co/mradermacher/airoboros-l2-c70b-3.1.2-GGUF/resolve/main/airoboros-l2-c70b-3.1.2.Q3_K_M.gguf) | Q3_K_M | 33.7 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/airoboros-l2-c70b-3.1.2-GGUF/resolve/main/airoboros-l2-c70b-3.1.2.Q3_K_L.gguf) | Q3_K_L | 36.6 | |
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| [GGUF](https://huggingface.co/mradermacher/airoboros-l2-c70b-3.1.2-GGUF/resolve/main/airoboros-l2-c70b-3.1.2.Q4_K_S.gguf) | Q4_K_S | 39.7 | fast, medium quality |
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| [GGUF](https://huggingface.co/mradermacher/airoboros-l2-c70b-3.1.2-GGUF/resolve/main/airoboros-l2-c70b-3.1.2.Q4_K_M.gguf) | Q4_K_M | 41.8 | fast, medium quality |
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| [GGUF](https://huggingface.co/mradermacher/airoboros-l2-c70b-3.1.2-GGUF/resolve/main/airoboros-l2-c70b-3.1.2.Q5_K_S.gguf) | Q5_K_S | 47.9 | |
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| [GGUF](https://huggingface.co/mradermacher/airoboros-l2-c70b-3.1.2-GGUF/resolve/main/airoboros-l2-c70b-3.1.2.Q5_K_M.gguf) | Q5_K_M | 49.2 | |
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| [PART 1](https://huggingface.co/mradermacher/airoboros-l2-c70b-3.1.2-GGUF/resolve/main/airoboros-l2-c70b-3.1.2.Q6_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/airoboros-l2-c70b-3.1.2-GGUF/resolve/main/airoboros-l2-c70b-3.1.2.Q6_K.gguf.part2of2) | Q6_K | 57.0 | very good quality |
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| [PART 1](https://huggingface.co/mradermacher/airoboros-l2-c70b-3.1.2-GGUF/resolve/main/airoboros-l2-c70b-3.1.2.Q8_0.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/airoboros-l2-c70b-3.1.2-GGUF/resolve/main/airoboros-l2-c70b-3.1.2.Q8_0.gguf.part2of2) | Q8_0 | 73.6 | fast, best quality |
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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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