81 lines
4.8 KiB
Markdown
81 lines
4.8 KiB
Markdown
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---
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base_model: mlabonne/Beagle14-7B
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language:
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- en
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library_name: transformers
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license: cc-by-nc-4.0
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quantized_by: mradermacher
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tags:
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- merge
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- mergekit
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- lazymergekit
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- fblgit/UNA-TheBeagle-7b-v1
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- argilla/distilabeled-Marcoro14-7B-slerp
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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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weighted/imatrix quants of https://huggingface.co/mlabonne/Beagle14-7B
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<!-- provided-files -->
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static quants are available at https://huggingface.co/mradermacher/Beagle14-7B-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/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-IQ1_S.gguf) | i1-IQ1_S | 1.7 | for the desperate |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-IQ1_M.gguf) | i1-IQ1_M | 1.9 | mostly desperate |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.1 | |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.3 | |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-IQ2_S.gguf) | i1-IQ2_S | 2.4 | |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-IQ2_M.gguf) | i1-IQ2_M | 2.6 | |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-Q2_K_S.gguf) | i1-Q2_K_S | 2.6 | very low quality |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-Q2_K.gguf) | i1-Q2_K | 2.8 | IQ3_XXS probably better |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 2.9 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 3.1 | |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.3 | IQ3_XS probably better |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-IQ3_S.gguf) | i1-IQ3_S | 3.3 | beats Q3_K* |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-IQ3_M.gguf) | i1-IQ3_M | 3.4 | |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 3.6 | IQ3_S probably better |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 3.9 | IQ3_M probably better |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 4.0 | |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-Q4_0.gguf) | i1-Q4_0 | 4.2 | fast, low quality |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.2 | optimal size/speed/quality |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 4.5 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-Q5_K_S.gguf) | i1-Q5_K_S | 5.1 | |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-Q5_K_M.gguf) | i1-Q5_K_M | 5.2 | |
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| [GGUF](https://huggingface.co/mradermacher/Beagle14-7B-i1-GGUF/resolve/main/Beagle14-7B.i1-Q6_K.gguf) | i1-Q6_K | 6.0 | 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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