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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: --> |
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<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS --> |
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<!-- ### quants_skip: --> |
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<!-- ### skip_mmproj: --> |
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static 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-GGUF).*** |
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weighted/imatrix quants are available at https://huggingface.co/mradermacher/Apollo-1-8B-i1-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-GGUF/resolve/main/Apollo-1-8B.Q2_K.gguf) | Q2_K | 3.4 | | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-GGUF/resolve/main/Apollo-1-8B.Q3_K_S.gguf) | Q3_K_S | 3.9 | | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-GGUF/resolve/main/Apollo-1-8B.Q3_K_M.gguf) | Q3_K_M | 4.2 | lower quality | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-GGUF/resolve/main/Apollo-1-8B.Q3_K_L.gguf) | Q3_K_L | 4.5 | | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-GGUF/resolve/main/Apollo-1-8B.IQ4_XS.gguf) | IQ4_XS | 4.7 | | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-GGUF/resolve/main/Apollo-1-8B.Q4_K_S.gguf) | Q4_K_S | 4.9 | fast, recommended | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-GGUF/resolve/main/Apollo-1-8B.Q4_K_M.gguf) | Q4_K_M | 5.1 | fast, recommended | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-GGUF/resolve/main/Apollo-1-8B.Q5_K_S.gguf) | Q5_K_S | 5.8 | | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-GGUF/resolve/main/Apollo-1-8B.Q5_K_M.gguf) | Q5_K_M | 6.0 | | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-GGUF/resolve/main/Apollo-1-8B.Q6_K.gguf) | Q6_K | 6.8 | very good quality | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-GGUF/resolve/main/Apollo-1-8B.Q8_0.gguf) | Q8_0 | 8.8 | fast, best quality | |
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| [GGUF](https://huggingface.co/mradermacher/Apollo-1-8B-GGUF/resolve/main/Apollo-1-8B.f16.gguf) | f16 | 16.5 | 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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