nekomata
Collection
The nekomata model series are based on the Qwen series and have been continually pre-trained on Japanese-specific corpora.
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8 items
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Updated
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5
rinna/nekomata-7b-gguf
The model is the GGUF version of rinna/nekomata-7b
. It can be used with 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
for details about model architecture and data.
Contributors
See llama.cpp for more usage details.
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}"
Please refer to rinna/nekomata-7b
for tokenization details.
@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}}
}