--- inference: false language: - zh - en license: unknown model_name: Rain-2x7B-MoE-32k-v0.2 pipeline_tag: text-generation prompt_template: ' SYS_PROMPT [INST] QUERY1 [/INST] RESPONSE1 [INST] QUERY2 [/INST]' 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 ---
# 小雨同學 2x7B 採用聯發科 Breeze 7B Instruct 為基底的國語 MoE (Mixture-of-Experts) 模型,共有兩個 Expert model。 請用 Marcoro14-7B 或是 Breeze-7B-Instruct 所推薦的 Prompt 格式進行操作;以下為模型配置。 - v0.2 更新了 tokenizer parameters ![](https://i.imgur.com/f3Ro6Fu.png) ### Rain-2x7B-MoE-32k-v0.2 This is an experimental Mixtral-architecture MoE model with 2 of 7B sized fine-tunes. Breeze and CodeNinja are used on top of [Marcoro14-7B-slerp](https://huggingface.co/mlabonne/Marcoro14-7B-slerp). Model configuration is as follows: * [Marcoro14-7B-slerp](https://huggingface.co/mlabonne/Marcoro14-7B-slerp) as base. * [Breeze-7B-Instruct-v0_1](https://huggingface.co/MediaTek-Research/Breeze-7B-Instruct-v0_1) as model 0. * [CodeNinja-1.0-OpenChat-7B](https://huggingface.co/beowolx/CodeNinja-1.0-OpenChat-7B) as model 1. To use the model, please use either prompt templates suggested by the base models. ## Notes Please evaluate before use in any application pipeline. Activation for coding part of the model would be `'code'`, `'python'`, `'typescript'`, `'javascript'`, `'programming'`, `'algorithm'`.