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Model: mradermacher/Qwen2-7b-Instruct-Boku-v3-GGUF Source: Original Platform
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Qwen2-7b-Instruct-Boku-v3.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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version https://git-lfs.github.com/spec/v1
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size 3574009760
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size 3499190176
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oid sha256:0b4a887439fd300dfeacbea7a05b16d20eb32d4f88111b20c50f49822e31f6c5
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size 3346253728
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version https://git-lfs.github.com/spec/v1
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oid sha256:1951b0012ea964f19e5f776f2a4de3e7d806e9f19835aade2882eaa3ffa86db0
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size 4250296224
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Qwen2-7b-Instruct-Boku-v3.Q2_K.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:e3fca78716704202debaaddaa68eb6c014a9decaf0d9d13d2abe423c370daec6
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size 3015937952
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Qwen2-7b-Instruct-Boku-v3.Q3_K_L.gguf
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oid sha256:1493ceb42f1d1f5f6c28a9daabfe747241282bcdcbad56e38bf29e8fe70088dd
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size 4088457120
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Qwen2-7b-Instruct-Boku-v3.Q3_K_M.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:b7fc7df9b1fdd2f18f3cb1d34a76ee534131fdbcf878567e551ba6ff70438667
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size 3808389024
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Qwen2-7b-Instruct-Boku-v3.Q3_K_S.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:2cbc16f7b79eac9344c638183dee42612da117e00c48fd59162c78c7226116f5
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size 3492366240
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Qwen2-7b-Instruct-Boku-v3.Q4_K_M.gguf
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oid sha256:977341f941be936ad22c29aa42d07ea1619df179db6cedd08fabbe10165a88fe
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size 4683071392
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size 4457766816
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size 5444829088
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size 5315174304
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size 8098523040
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README.md
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---
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base_model: Akimite/Qwen2-7b-Instruct-Boku-v3
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language:
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- ja
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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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<!-- ### 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/Akimite/Qwen2-7b-Instruct-Boku-v3
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<!-- provided-files -->
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weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
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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/Qwen2-7b-Instruct-Boku-v3-GGUF/resolve/main/Qwen2-7b-Instruct-Boku-v3.Q2_K.gguf) | Q2_K | 3.1 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2-7b-Instruct-Boku-v3-GGUF/resolve/main/Qwen2-7b-Instruct-Boku-v3.IQ3_XS.gguf) | IQ3_XS | 3.4 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2-7b-Instruct-Boku-v3-GGUF/resolve/main/Qwen2-7b-Instruct-Boku-v3.Q3_K_S.gguf) | Q3_K_S | 3.6 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2-7b-Instruct-Boku-v3-GGUF/resolve/main/Qwen2-7b-Instruct-Boku-v3.IQ3_S.gguf) | IQ3_S | 3.6 | beats Q3_K* |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2-7b-Instruct-Boku-v3-GGUF/resolve/main/Qwen2-7b-Instruct-Boku-v3.IQ3_M.gguf) | IQ3_M | 3.7 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2-7b-Instruct-Boku-v3-GGUF/resolve/main/Qwen2-7b-Instruct-Boku-v3.Q3_K_M.gguf) | Q3_K_M | 3.9 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2-7b-Instruct-Boku-v3-GGUF/resolve/main/Qwen2-7b-Instruct-Boku-v3.Q3_K_L.gguf) | Q3_K_L | 4.2 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2-7b-Instruct-Boku-v3-GGUF/resolve/main/Qwen2-7b-Instruct-Boku-v3.IQ4_XS.gguf) | IQ4_XS | 4.4 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2-7b-Instruct-Boku-v3-GGUF/resolve/main/Qwen2-7b-Instruct-Boku-v3.Q4_K_S.gguf) | Q4_K_S | 4.6 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2-7b-Instruct-Boku-v3-GGUF/resolve/main/Qwen2-7b-Instruct-Boku-v3.Q4_K_M.gguf) | Q4_K_M | 4.8 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2-7b-Instruct-Boku-v3-GGUF/resolve/main/Qwen2-7b-Instruct-Boku-v3.Q5_K_S.gguf) | Q5_K_S | 5.4 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2-7b-Instruct-Boku-v3-GGUF/resolve/main/Qwen2-7b-Instruct-Boku-v3.Q5_K_M.gguf) | Q5_K_M | 5.5 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2-7b-Instruct-Boku-v3-GGUF/resolve/main/Qwen2-7b-Instruct-Boku-v3.Q6_K.gguf) | Q6_K | 6.4 | very good quality |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2-7b-Instruct-Boku-v3-GGUF/resolve/main/Qwen2-7b-Instruct-Boku-v3.Q8_0.gguf) | Q8_0 | 8.2 | fast, best quality |
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| [GGUF](https://huggingface.co/mradermacher/Qwen2-7b-Instruct-Boku-v3-GGUF/resolve/main/Qwen2-7b-Instruct-Boku-v3.f16.gguf) | f16 | 15.3 | 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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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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<!-- end -->
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