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---
thumbnail: https://github.com/rinnakk/japanese-pretrained-models/blob/master/rinna.png
license: llama2
datasets:
- mc4
- cc100
- oscar
- wikipedia
- EleutherAI/pile
language:
- ja
- en
inference: false
---
# `rinna/youri-7b-gptq`
# Overview
`rinna/youri-7b-gptq` is the quantized model for [`rinna/youri-7b`](https://huggingface.co/rinna/youri-7b) using AutoGPTQ. The quantized version is 4x smaller than the original model and thus requires less memory and provides faster inference.
* **Library**
Refer to the [original model](https://huggingface.co/rinna/youri-7b) for library details.
* **Model architecture**
Refer to the [original model](https://huggingface.co/rinna/youri-7b) for architecture details.
* **Continual pre-training**
Refer to the [original model](https://huggingface.co/rinna/youri-7b) for pre-training details.
* **Contributors**
- [Toshiaki Wakatsuki](https://huggingface.co/t-w)
- [Tianyu Zhao](https://huggingface.co/tianyuz)
- [Kei Sawada](https://huggingface.co/keisawada)
---
# Benchmarking
Please refer to [rinna's LM benchmark page](https://rinnakk.github.io/research/benchmarks/lm/index.html).
---
# How to use the model
~~~~python
import torch
from transformers import AutoTokenizer
from auto_gptq import AutoGPTQForCausalLM
tokenizer = AutoTokenizer.from_pretrained("rinna/youri-7b-gptq")
model = AutoGPTQForCausalLM.from_quantized("rinna/youri-7b-gptq", use_safetensors=True)
text = "西田幾多郎は、"
token_ids = tokenizer.encode(text, add_special_tokens=False, return_tensors="pt")
with torch.no_grad():
output_ids = model.generate(
input_ids=token_ids.to(model.device),
max_new_tokens=200,
min_new_tokens=200,
do_sample=True,
temperature=1.0,
top_p=0.95,
pad_token_id=tokenizer.pad_token_id,
bos_token_id=tokenizer.bos_token_id,
eos_token_id=tokenizer.eos_token_id
)
output = tokenizer.decode(output_ids.tolist()[0])
print(output)
~~~~
---
# Tokenization
The model uses the original llama-2 tokenizer.
---
# How to cite
~~~
@misc{rinna-youri-7b-gptq,
title = {rinna/youri-7b-gptq},
author={Wakatsuki, Toshiaki and Zhao, Tianyu and Sawada, Kei}
url = {https://huggingface.co/rinna/youri-7b-gptq},
}
@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},
url = {https://arxiv.org/abs/2404.01657},
}
~~~
---
# License
[The llama2 license](https://ai.meta.com/llama/license/) |