97 lines
5.6 KiB
Markdown
97 lines
5.6 KiB
Markdown
---
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base_model: rubenroy/Geneva-12B-GCv2-500k
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datasets:
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- rubenroy/GammaCorpus-v2-500k
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language:
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- en
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- fr
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- de
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- es
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- it
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- pt
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- ru
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- zh
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- ja
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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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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- trl
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- gammacorpus
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- geneva
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- chat
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- mistral
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- conversational
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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/rubenroy/Geneva-12B-GCv2-500k
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<!-- provided-files -->
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static quants are available at https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-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/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-IQ1_S.gguf) | i1-IQ1_S | 3.1 | for the desperate |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-IQ1_M.gguf) | i1-IQ1_M | 3.3 | mostly desperate |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 3.7 | |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-IQ2_XS.gguf) | i1-IQ2_XS | 4.0 | |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-IQ2_S.gguf) | i1-IQ2_S | 4.2 | |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-IQ2_M.gguf) | i1-IQ2_M | 4.5 | |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-Q2_K_S.gguf) | i1-Q2_K_S | 4.6 | very low quality |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-Q2_K.gguf) | i1-Q2_K | 4.9 | IQ3_XXS probably better |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 5.0 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-IQ3_XS.gguf) | i1-IQ3_XS | 5.4 | |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-Q3_K_S.gguf) | i1-Q3_K_S | 5.6 | IQ3_XS probably better |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-IQ3_S.gguf) | i1-IQ3_S | 5.7 | beats Q3_K* |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-IQ3_M.gguf) | i1-IQ3_M | 5.8 | |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-Q3_K_M.gguf) | i1-Q3_K_M | 6.2 | IQ3_S probably better |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-Q3_K_L.gguf) | i1-Q3_K_L | 6.7 | IQ3_M probably better |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-IQ4_XS.gguf) | i1-IQ4_XS | 6.8 | |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-Q4_0.gguf) | i1-Q4_0 | 7.2 | fast, low quality |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-IQ4_NL.gguf) | i1-IQ4_NL | 7.2 | prefer IQ4_XS |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-Q4_K_S.gguf) | i1-Q4_K_S | 7.2 | optimal size/speed/quality |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-Q4_K_M.gguf) | i1-Q4_K_M | 7.6 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-Q4_1.gguf) | i1-Q4_1 | 7.9 | |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-Q5_K_S.gguf) | i1-Q5_K_S | 8.6 | |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-Q5_K_M.gguf) | i1-Q5_K_M | 8.8 | |
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| [GGUF](https://huggingface.co/mradermacher/Geneva-12B-GCv2-500k-i1-GGUF/resolve/main/Geneva-12B-GCv2-500k.i1-Q6_K.gguf) | i1-Q6_K | 10.2 | 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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