--- base_model: allknowingroger/Multimerge-19B-pass language: - en library_name: transformers license: apache-2.0 quantized_by: mradermacher tags: - merge - mergekit - lazymergekit - allknowingroger/Multimerge-12B-MoE --- ## About static quants of https://huggingface.co/allknowingroger/Multimerge-19B-pass weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion. ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Provided Quants (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) | Link | Type | Size/GB | Notes | |:-----|:-----|--------:|:------| | [GGUF](https://huggingface.co/mradermacher/Multimerge-19B-pass-GGUF/resolve/main/Multimerge-19B-pass.Q2_K.gguf) | Q2_K | 7.2 | | | [GGUF](https://huggingface.co/mradermacher/Multimerge-19B-pass-GGUF/resolve/main/Multimerge-19B-pass.IQ3_XS.gguf) | IQ3_XS | 8.0 | | | [GGUF](https://huggingface.co/mradermacher/Multimerge-19B-pass-GGUF/resolve/main/Multimerge-19B-pass.Q3_K_S.gguf) | Q3_K_S | 8.4 | | | [GGUF](https://huggingface.co/mradermacher/Multimerge-19B-pass-GGUF/resolve/main/Multimerge-19B-pass.IQ3_S.gguf) | IQ3_S | 8.4 | beats Q3_K* | | [GGUF](https://huggingface.co/mradermacher/Multimerge-19B-pass-GGUF/resolve/main/Multimerge-19B-pass.IQ3_M.gguf) | IQ3_M | 8.6 | | | [GGUF](https://huggingface.co/mradermacher/Multimerge-19B-pass-GGUF/resolve/main/Multimerge-19B-pass.Q3_K_M.gguf) | Q3_K_M | 9.3 | lower quality | | [GGUF](https://huggingface.co/mradermacher/Multimerge-19B-pass-GGUF/resolve/main/Multimerge-19B-pass.Q3_K_L.gguf) | Q3_K_L | 10.1 | | | [GGUF](https://huggingface.co/mradermacher/Multimerge-19B-pass-GGUF/resolve/main/Multimerge-19B-pass.IQ4_XS.gguf) | IQ4_XS | 10.5 | | | [GGUF](https://huggingface.co/mradermacher/Multimerge-19B-pass-GGUF/resolve/main/Multimerge-19B-pass.Q4_K_S.gguf) | Q4_K_S | 11.0 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/Multimerge-19B-pass-GGUF/resolve/main/Multimerge-19B-pass.Q4_K_M.gguf) | Q4_K_M | 11.7 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/Multimerge-19B-pass-GGUF/resolve/main/Multimerge-19B-pass.Q5_K_S.gguf) | Q5_K_S | 13.3 | | | [GGUF](https://huggingface.co/mradermacher/Multimerge-19B-pass-GGUF/resolve/main/Multimerge-19B-pass.Q5_K_M.gguf) | Q5_K_M | 13.7 | | | [GGUF](https://huggingface.co/mradermacher/Multimerge-19B-pass-GGUF/resolve/main/Multimerge-19B-pass.Q6_K.gguf) | Q6_K | 15.8 | very good quality | | [GGUF](https://huggingface.co/mradermacher/Multimerge-19B-pass-GGUF/resolve/main/Multimerge-19B-pass.Q8_0.gguf) | Q8_0 | 20.5 | fast, best quality | Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better): ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png) And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 ## FAQ / Model Request See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized. ## Thanks I thank my company, [nethype GmbH](https://www.nethype.de/), for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.