--- inference: false language: - zh - en license: unknown model_name: Chihiro-7B-v0.1 pipeline_tag: text-generation prompt_template: ' SYS_PROMPT [INST] QUERY1 [/INST] RESPONSE1 [INST] QUERY2 [/INST]' quantized_by: yuuko-eth tags: - nlp - chinese - mistral - traditional_chinese - merge - mergekit - MediaTek-Research/Breeze-7B-Instruct-v0_1 - mlabonne/Zebrafish-7B --- # Chihiro-7B-v0.1-GGUF - Model creator: [yuuko-eth](https://huggingface.co/yuuko-eth) - Original model: [Chihiro-7B-v0.1](https://huggingface.co/yuuko-eth/Chihiro-7B-v0.1) ## Description This repo contains GGUF format model files for [Chihiro-7B-v0.1](https://huggingface.co/yuuko-eth/Chihiro-7B-v0.1). ### About GGUF GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. Here is an incomplete list of clients and libraries that are known to support GGUF: * [llama.cpp](https://github.com/ggerganov/llama.cpp). The source project for GGUF. Offers a CLI and a server option. * [text-generation-webui](https://github.com/oobabooga/text-generation-webui), the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration. * [KoboldCpp](https://github.com/LostRuins/koboldcpp), a fully featured web UI, with GPU accel across all platforms and GPU architectures. Especially good for story telling. * [GPT4All](https://gpt4all.io/index.html), a free and open source local running GUI, supporting Windows, Linux and macOS with full GPU accel. * [LM Studio](https://lmstudio.ai/), an easy-to-use and powerful local GUI for Windows and macOS (Silicon), with GPU acceleration. Linux available, in beta as of 27/11/2023. * [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui), a great web UI with many interesting and unique features, including a full model library for easy model selection. * [Faraday.dev](https://faraday.dev/), an attractive and easy to use character-based chat GUI for Windows and macOS (both Silicon and Intel), with GPU acceleration. * [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), a Python library with GPU accel, LangChain support, and OpenAI-compatible API server. * [candle](https://github.com/huggingface/candle), a Rust ML framework with a focus on performance, including GPU support, and ease of use. * [ctransformers](https://github.com/marella/ctransformers), a Python library with GPU accel, LangChain support, and OpenAI-compatible AI server. Note, as of time of writing (November 27th 2023), ctransformers has not been updated in a long time and does not support many recent models. --- > Original `README.MD` is as follows. ---
# 千尋 7B v0.1 Zebrafish 7B 加上 Breeze 7B 的 slerp merge 試驗性通用繁中基座模型 📚 GGUF Quants 👉 [Chihiro-7B-v0.1-GGUF](https://huggingface.co/yuuko-eth/Chihiro-7B-v0.1-GGUF) 請用 Mistral 7B Instruct 或是 Breeze 7B Instruct 所推薦的 Prompt 格式進行操作;以下為模型配置。 ![](https://i.imgur.com/UwNO4fS.png) ### Chihiro 7B v0.1 This is an experimental Mistral-architecture SLERP merge with two brilliant base models. Zebrafish and Breeze were used together in this work. Model configuration is as follows: * [Breeze-7B-Instruct](https://huggingface.co/MediaTek-Research/Breeze-7B-Instruct-v0_1) as base. * [Zebrafish-7B](https://huggingface.co/mlabonne/Zebrafish-7B) as model 1. To use the model, please use either prompt templates suggested by the base models, or just slap the Mistral one on.

### Benchmarks Evaluation suite: OpenLLM | Model | ARC |HellaSwag| MMLU |TruthfulQA|Winogrande|GSM8K| |-------------------------------------------------------------------|----:|--------:|--------------------------|---------:|---------:|----:| |[Chihiro-7B-v0.1](https://huggingface.co/yuuko-eth/Chihiro-7B-v0.1)|68.52| 85.95| (not yet evaluated) | 63.81| 81.77|64.22| Evaluation suite: Nous | Model |AGIEval|GPT4All|TruthfulQA|Bigbench|Average| |-------------------------------------------------------------------|------:|------:|---------:|-------:|------:| |[Chihiro-7B-v0.1](https://huggingface.co/yuuko-eth/Chihiro-7B-v0.1)| 45.16| 75.26| 63.82| 47.38| 57.91| Average: 47.38% Average score: 57.91% Evaluated Apr. 27, 2024, NVIDIA RTX 4090