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---
thumbnail: https://github.com/rinnakk/japanese-pretrained-models/blob/master/rinna.png
language:
- ja
- en
tags:
- qwen
inference: false
license: other
license_name: tongyi-qianwen-license-agreement
license_link: >-
https://github.com/QwenLM/Qwen/blob/main/Tongyi%20Qianwen%20LICENSE%20AGREEMENT
pipeline_tag: text-generation
base_model: rinna/nekomata-7b
base_model_relation: quantized
---
# `rinna/nekomata-7b-gguf`
# Overview
The model is the GGUF version of [`rinna/nekomata-7b`](https://huggingface.co./rinna/nekomata-7b). It can be used with [llama.cpp](https://github.com/ggerganov/llama.cpp) for lightweight inference.
Quantization of this model may cause stability issue in GPTQ, AWQ and GGUF q4_0. We recommend **GGUF q4_K_M** for 4-bit quantization.
See [`rinna/nekomata-7b`](https://huggingface.co./rinna/nekomata-7b) for details about model architecture and data.
* **Contributors**
- [Toshiaki Wakatsuki](https://huggingface.co./t-w)
- [Tianyu Zhao](https://huggingface.co./tianyuz)
- [Kei Sawada](https://huggingface.co./keisawada)
---
# How to use the model
See [llama.cpp](https://github.com/ggerganov/llama.cpp) for more usage details.
~~~~bash
git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp
make
MODEL_PATH=/path/to/nekomata-7b-gguf/nekomata-7b.Q4_K_M.gguf
MAX_N_TOKENS=128
PROMPT="西田幾多郎は、"
./main -m ${MODEL_PATH} -n ${MAX_N_TOKENS} -p "${PROMPT}"
~~~~
---
# Tokenization
Please refer to [`rinna/nekomata-7b`](https://huggingface.co./rinna/nekomata-7b) for tokenization details.
---
# How to cite
```bibtex
@misc{rinna-nekomata-7b-gguf,
title = {rinna/nekomata-7b-gguf},
author = {Wakatsuki, Toshiaki and Zhao, Tianyu and Sawada, Kei},
url = {https://huggingface.co./rinna/nekomata-7b-gguf}
}
@inproceedings{sawada2024release,
title = {Release of Pre-Trained Models for the {J}apanese Language},
author = {Sawada, Kei and Zhao, Tianyu and Shing, Makoto and Mitsui, Kentaro and Kaga, Akio and Hono, Yukiya and Wakatsuki, Toshiaki and Mitsuda, Koh},
booktitle = {Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)},
month = {5},
year = {2024},
pages = {13898--13905},
url = {https://aclanthology.org/2024.lrec-main.1213},
note = {\url{https://arxiv.org/abs/2404.01657}}
}
```
---
# License
[Tongyi Qianwen LICENSE AGREEMENT](https://github.com/QwenLM/Qwen/blob/main/Tongyi%20Qianwen%20LICENSE%20AGREEMENT) |