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Model: mradermacher/salamandra-2b-instruct-aina-hack-GGUF Source: Original Platform
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salamandra-2b-instruct-aina-hack.Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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---
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base_model: BSC-LT/salamandra-2b-instruct-aina-hack
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language:
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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/BSC-LT/salamandra-2b-instruct-aina-hack
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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/salamandra-2b-instruct-aina-hack-GGUF/resolve/main/salamandra-2b-instruct-aina-hack.Q2_K.gguf) | Q2_K | 1.2 | |
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| [GGUF](https://huggingface.co/mradermacher/salamandra-2b-instruct-aina-hack-GGUF/resolve/main/salamandra-2b-instruct-aina-hack.Q3_K_S.gguf) | Q3_K_S | 1.3 | |
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| [GGUF](https://huggingface.co/mradermacher/salamandra-2b-instruct-aina-hack-GGUF/resolve/main/salamandra-2b-instruct-aina-hack.Q3_K_M.gguf) | Q3_K_M | 1.4 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/salamandra-2b-instruct-aina-hack-GGUF/resolve/main/salamandra-2b-instruct-aina-hack.Q3_K_L.gguf) | Q3_K_L | 1.4 | |
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| [GGUF](https://huggingface.co/mradermacher/salamandra-2b-instruct-aina-hack-GGUF/resolve/main/salamandra-2b-instruct-aina-hack.IQ4_XS.gguf) | IQ4_XS | 1.5 | |
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| [GGUF](https://huggingface.co/mradermacher/salamandra-2b-instruct-aina-hack-GGUF/resolve/main/salamandra-2b-instruct-aina-hack.Q4_0_4_4.gguf) | Q4_0_4_4 | 1.5 | fast on arm, low quality |
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| [GGUF](https://huggingface.co/mradermacher/salamandra-2b-instruct-aina-hack-GGUF/resolve/main/salamandra-2b-instruct-aina-hack.Q4_K_S.gguf) | Q4_K_S | 1.5 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/salamandra-2b-instruct-aina-hack-GGUF/resolve/main/salamandra-2b-instruct-aina-hack.Q4_K_M.gguf) | Q4_K_M | 1.6 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/salamandra-2b-instruct-aina-hack-GGUF/resolve/main/salamandra-2b-instruct-aina-hack.Q5_K_S.gguf) | Q5_K_S | 1.7 | |
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| [GGUF](https://huggingface.co/mradermacher/salamandra-2b-instruct-aina-hack-GGUF/resolve/main/salamandra-2b-instruct-aina-hack.Q5_K_M.gguf) | Q5_K_M | 1.8 | |
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| [GGUF](https://huggingface.co/mradermacher/salamandra-2b-instruct-aina-hack-GGUF/resolve/main/salamandra-2b-instruct-aina-hack.Q6_K.gguf) | Q6_K | 2.0 | very good quality |
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| [GGUF](https://huggingface.co/mradermacher/salamandra-2b-instruct-aina-hack-GGUF/resolve/main/salamandra-2b-instruct-aina-hack.Q8_0.gguf) | Q8_0 | 2.5 | fast, best quality |
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| [GGUF](https://huggingface.co/mradermacher/salamandra-2b-instruct-aina-hack-GGUF/resolve/main/salamandra-2b-instruct-aina-hack.f16.gguf) | f16 | 4.6 | 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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version https://git-lfs.github.com/spec/v1
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oid sha256:ee2ae9f656f0a7c717025e911f777632edce3d09c72c5eaff3ed5ac6670ecf08
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size 1370138528
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version https://git-lfs.github.com/spec/v1
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oid sha256:a4cd11d6ce0f84a10f10a2a20c43b5d6d4b2741ce41532db71190bca2eab3acb
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size 1087408032
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size 1317455776
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oid sha256:f8775376df339c4a785db5e888c501fb45b374cb5bc4e873a43b3cb5452d8fe6
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size 1277323168
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oid sha256:5701433ec030fc2564bae9e77598a84aeb7d4823e8be8e91e447f208e7e74573
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size 1215416224
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oid sha256:f9caffca9ea4ef8b14ea7e8a2bc05675b4e28bf2d226fa1b172ea20782367cfd
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size 1409550240
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oid sha256:d2cfe2cb8e6ae052afd3b9eecef82812b64f810163df2a401deb5a7145485013
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size 1506084768
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oid sha256:5a70b87acb97f7e6043bd7cbdbe7f6a82e754cc72afc6846b423e94f9af4e63e
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size 1447159712
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oid sha256:924ab622b555344a4f42f4a5fa679e0a85b5f0582f4344be231d7c41e8d61b9b
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size 1690863520
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oid sha256:5c4dd782041510d5b7e9a793bae48082a1fd9c7023bddbc83a967a0f7c9b0aae
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size 1642399648
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version https://git-lfs.github.com/spec/v1
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oid sha256:c9a624915f5bf1aecfc4d4ef284f65aaa1b6c00d6e1104e2d4dc663ae12036b4
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size 1920092064
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version https://git-lfs.github.com/spec/v1
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oid sha256:4a41b49dd8516089cd978e013ee936bea1cc3c10832260b8b2cb4edaa67f664e
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size 2401077152
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oid sha256:03d720e1a2336f220461c8a3a6db23c52e447bb1ec61d67c660b3b11605b9ee0
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size 4513630112
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