--- base_model: ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.3 language: - en library_name: transformers license: apache-2.0 quantized_by: mradermacher --- ## About static quants of https://huggingface.co/ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.3 weighted/imatrix quants are available at https://huggingface.co/mradermacher/Mistral-Nemo-12B-ArliAI-RPMax-v1.3-i1-GGUF ## 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/Mistral-Nemo-12B-ArliAI-RPMax-v1.3-GGUF/resolve/main/Mistral-Nemo-12B-ArliAI-RPMax-v1.3.Q2_K.gguf) | Q2_K | 4.9 | | | [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-12B-ArliAI-RPMax-v1.3-GGUF/resolve/main/Mistral-Nemo-12B-ArliAI-RPMax-v1.3.Q3_K_S.gguf) | Q3_K_S | 5.6 | | | [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-12B-ArliAI-RPMax-v1.3-GGUF/resolve/main/Mistral-Nemo-12B-ArliAI-RPMax-v1.3.Q3_K_M.gguf) | Q3_K_M | 6.2 | lower quality | | [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-12B-ArliAI-RPMax-v1.3-GGUF/resolve/main/Mistral-Nemo-12B-ArliAI-RPMax-v1.3.Q4_K_S.gguf) | Q4_K_S | 7.2 | fast, recommended | 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. 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.