--- base_model: yuuko-eth/Rain-2x7B-MoE-32k-v0.1 language: - zh - en library_name: transformers license: unknown model_name: Rain-2x7B-MoE-32k-v0.1 prompt_template: SYS_PROMPT [INST] QUERY1 [/INST] RESPONSE1 [INST] QUERY2 [/INST] quantized_by: mradermacher tags: - nlp - chinese - mistral - mixtral - traditional_chinese - merge - mergekit - MediaTek-Research/Breeze-7B-Instruct-v0_1 - beowolx/CodeNinja-1.0-OpenChat-7B - mlabonne/Marcoro14-7B-slerp --- ## About weighted/imatrix quants of https://huggingface.co/yuuko-eth/Rain-2x7B-MoE-32k-v0.1 static quants are available at https://huggingface.co/mradermacher/Rain-2x7B-MoE-32k-v0.1-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/Rain-2x7B-MoE-32k-v0.1-i1-GGUF/resolve/main/Rain-2x7B-MoE-32k-v0.1.i1-Q2_K.gguf) | i1-Q2_K | 4.9 | IQ3_XXS probably better | | [GGUF](https://huggingface.co/mradermacher/Rain-2x7B-MoE-32k-v0.1-i1-GGUF/resolve/main/Rain-2x7B-MoE-32k-v0.1.i1-IQ3_M.gguf) | i1-IQ3_M | 5.8 | | | [GGUF](https://huggingface.co/mradermacher/Rain-2x7B-MoE-32k-v0.1-i1-GGUF/resolve/main/Rain-2x7B-MoE-32k-v0.1.i1-Q4_K_S.gguf) | i1-Q4_K_S | 7.4 | optimal size/speed/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. 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.