202 lines
6.3 KiB
Markdown
202 lines
6.3 KiB
Markdown
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---
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base_model: Loom-Labs/Apollo-1-8B
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language:
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- en
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- fr
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- pt
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- de
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- ro
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- sv
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- da
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- bg
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- ru
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- cs
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- el
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- uk
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- es
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- nl
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- sk
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- hr
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- pl
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- lt
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- nb
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- nn
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- fa
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- sl
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- gu
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- lv
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- it
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- oc
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- ne
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- mr
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- be
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- sr
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- lb
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- vec
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- as
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- cy
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- szl
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- ast
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- hne
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- awa
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- mai
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- bho
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- sd
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- ga
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- fo
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- hi
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- pa
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- bn
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- or
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- tg
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- yi
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- lmo
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- lij
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- scn
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- fur
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- sc
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- gl
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- ca
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- is
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- sq
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- li
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- prs
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- af
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- mk
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- si
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- ur
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- mag
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- bs
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- hy
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- zh
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- yue
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- my
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- ar
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- he
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- mt
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- id
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- ms
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- tl
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- ceb
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- jv
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- su
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- min
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- ban
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- pag
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- ilo
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- war
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- ta
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- te
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- kn
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- ml
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- tr
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- az
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- uz
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- kk
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- ba
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- tt
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- th
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- lo
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- fi
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- et
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- hu
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- vi
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- km
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- ja
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- ko
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- ka
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- eu
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- ht
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- pap
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- kea
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- tpi
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- sw
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library_name: transformers
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license: other
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license_link: https://huggingface.co/apexion-ai/Nous-V1-8B/blob/main/LICENSE.md
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license_name: anvdl-1.0
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mradermacher:
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readme_rev: 1
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quantized_by: mradermacher
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- qwen3
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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: nicoboss -->
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<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S -->
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<!-- ### quants_skip: -->
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<!-- ### skip_mmproj: -->
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weighted/imatrix quants of https://huggingface.co/Loom-Labs/Apollo-1-8B
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<!-- provided-files -->
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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Apollo-1-8B-i1-GGUF).***
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static quants are available at https://huggingface.co/mradermacher/Apollo-1-8B-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/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-IQ1_S.gguf) | i1-IQ1_S | 2.2 | for the desperate |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-IQ1_M.gguf) | i1-IQ1_M | 2.4 | mostly desperate |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.6 | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.8 | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-IQ2_S.gguf) | i1-IQ2_S | 3.0 | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-IQ2_M.gguf) | i1-IQ2_M | 3.2 | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-Q2_K_S.gguf) | i1-Q2_K_S | 3.2 | very low quality |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-Q2_K.gguf) | i1-Q2_K | 3.4 | IQ3_XXS probably better |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 3.5 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 3.7 | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.9 | IQ3_XS probably better |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-IQ3_S.gguf) | i1-IQ3_S | 3.9 | beats Q3_K* |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-IQ3_M.gguf) | i1-IQ3_M | 4.0 | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 4.2 | IQ3_S probably better |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 4.5 | IQ3_M probably better |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 4.7 | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-Q4_0.gguf) | i1-Q4_0 | 4.9 | fast, low quality |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-IQ4_NL.gguf) | i1-IQ4_NL | 4.9 | prefer IQ4_XS |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.9 | optimal size/speed/quality |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 5.1 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-Q4_1.gguf) | i1-Q4_1 | 5.3 | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-Q5_K_S.gguf) | i1-Q5_K_S | 5.8 | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-Q5_K_M.gguf) | i1-Q5_K_M | 6.0 | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-i1-GGUF/resolve/main/Apollo-1-8B.i1-Q6_K.gguf) | i1-Q6_K | 6.8 | 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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## 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. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.
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