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---
license: cc
language:
- ja
library_name: transformers
pipeline_tag: text-generation
tags:
- japanese
- llama-2
- instruction-tuning
---
# Stockmark-13b-instruct
**Stockmark-13b-instruct** is an instruction-tuned version of [Stockmark-13b](https://huggingface.co/stockmark/stockmark-13b), a 13 billion parameter Japanese LLM. This model is developed by [Stockmark Inc.](https://stockmark.co.jp/)
We used data (2023/11/03 version) from [Project of Development of Japanese Instruction data for LLM](https://liat-aip.sakura.ne.jp/wp/llm%E3%81%AE%E3%81%9F%E3%82%81%E3%81%AE%E6%97%A5%E6%9C%AC%E8%AA%9E%E3%82%A4%E3%83%B3%E3%82%B9%E3%83%88%E3%83%A9%E3%82%AF%E3%82%B7%E3%83%A7%E3%83%B3%E3%83%87%E3%83%BC%E3%82%BF%E4%BD%9C%E6%88%90/) for instruction tuning.
This model is licensed under non-commercial license.
Please see our [blog](https://tech.stockmark.co.jp/blog/202311_stockmark_13b_instruct/) for more details.
## How to use
```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("stockmark/stockmark-13b-instruct", device_map="auto", torch_dtype=torch.bfloat16)
tokenizer = AutoTokenizer.from_pretrained("stockmark/stockmark-13b-instruct")
instruction = "自然言語処理とは?"
prompt = f"""### Input:
{instruction}
### Output:
"""
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
with torch.no_grad():
tokens = model.generate(
**inputs,
max_new_tokens=128,
do_sample=True,
temperature=0.7
)
output = tokenizer.decode(tokens[0], skip_special_tokens=True)
print(output)
```
## Training dataset
[Project of Development of Japanese Instruction data for LLM](https://liat-aip.sakura.ne.jp/wp/llm%E3%81%AE%E3%81%9F%E3%82%81%E3%81%AE%E6%97%A5%E6%9C%AC%E8%AA%9E%E3%82%A4%E3%83%B3%E3%82%B9%E3%83%88%E3%83%A9%E3%82%AF%E3%82%B7%E3%83%A7%E3%83%B3%E3%83%87%E3%83%BC%E3%82%BF%E4%BD%9C%E6%88%90/)
## License
[CC BY-NC-SA](https://creativecommons.org/licenses/by-nc-sa/4.0/)
## Developed by
[Stockmark Inc.](https://stockmark.co.jp/)
## Author
[Takahiro Omi](https://huggingface.co/omitakahiro) |