128 lines
6.6 KiB
Markdown
128 lines
6.6 KiB
Markdown
---
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base_model: aifeifei798/EuroLLM-22B-Instruct-2512-FT
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datasets:
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- aifeifei798/EuroBlocks_Sampled_100
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language:
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- en
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- de
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- es
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- fr
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- it
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- pt
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- pl
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- nl
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- tr
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- sv
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- cs
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- el
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- hu
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- ro
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- fi
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- uk
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- sl
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- sk
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- da
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- lt
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- lv
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- et
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- bg
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- no
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- ca
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- hr
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- ga
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- mt
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- gl
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- zh
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- ru
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- ko
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- ja
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- ar
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- hi
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library_name: transformers
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license: apache-2.0
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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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- EuroLLM
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- llama
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- philosophy
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- text
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- roleplay
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- mental-health-helper
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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/aifeifei798/EuroLLM-22B-Instruct-2512-FT
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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#EuroLLM-22B-Instruct-2512-FT-i1-GGUF).***
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static quants are available at https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-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/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-IQ1_S.gguf) | i1-IQ1_S | 5.4 | for the desperate |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-IQ1_M.gguf) | i1-IQ1_M | 5.8 | mostly desperate |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 6.5 | |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-IQ2_XS.gguf) | i1-IQ2_XS | 7.1 | |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-IQ2_S.gguf) | i1-IQ2_S | 7.5 | |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-IQ2_M.gguf) | i1-IQ2_M | 8.1 | |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-Q2_K_S.gguf) | i1-Q2_K_S | 8.1 | very low quality |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-Q2_K.gguf) | i1-Q2_K | 8.8 | IQ3_XXS probably better |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 9.1 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-IQ3_XS.gguf) | i1-IQ3_XS | 9.7 | |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-Q3_K_S.gguf) | i1-Q3_K_S | 10.1 | IQ3_XS probably better |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-IQ3_S.gguf) | i1-IQ3_S | 10.2 | beats Q3_K* |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-IQ3_M.gguf) | i1-IQ3_M | 10.5 | |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-Q3_K_M.gguf) | i1-Q3_K_M | 11.2 | IQ3_S probably better |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-Q3_K_L.gguf) | i1-Q3_K_L | 12.2 | IQ3_M probably better |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-IQ4_XS.gguf) | i1-IQ4_XS | 12.4 | |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-Q4_0.gguf) | i1-Q4_0 | 13.1 | fast, low quality |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-Q4_K_S.gguf) | i1-Q4_K_S | 13.1 | optimal size/speed/quality |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-Q4_K_M.gguf) | i1-Q4_K_M | 13.8 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-Q4_1.gguf) | i1-Q4_1 | 14.4 | |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-Q5_K_S.gguf) | i1-Q5_K_S | 15.8 | |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-Q5_K_M.gguf) | i1-Q5_K_M | 16.1 | |
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| [GGUF](https://huggingface.co/mradermacher/EuroLLM-22B-Instruct-2512-FT-i1-GGUF/resolve/main/EuroLLM-22B-Instruct-2512-FT.i1-Q6_K.gguf) | i1-Q6_K | 18.7 | 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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<!-- end -->
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