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---
license: cc-by-nc-4.0
---
# tsubaki-10b
# Overview
This repository provides a Japanese-centric multilingual GPT-NeoX model of 10 billion parameters.
* **Library**
The model was trained using code based on [EleutherAI/gpt-neox](https://github.com/EleutherAI/gpt-neox).
* **Model architecture**
A 36-layer, 4864-hidden-size transformer-based language model.
* **Pre-training**
The model was trained on around **600B** tokens from a mixture of the following corpora
- [Japanese C4](https://huggingface.co/datasets/mc4)
- [The Pile](https://huggingface.co/datasets/EleutherAI/pile)
* **Model Series**
| Variant | Link |
| :-- | :--|
| tsubaki-10b-instruction-sft | https://huggingface.co/Kojima777/tsubaki-10b-instruction-sft |
| tsubaki-10b | https://huggingface.co/Kojima777/tsubaki-10b |
* **Authors**
Takeshi Kojima
---
# Benchmarking
* **Japanese benchmark**
- *The 4-task average accuracy is based on results of JCommonsenseQA, JNLI, MARC-ja, and JSQuAD.*
| Model | Average | JCommonsenseQA | JNLI | MARC-ja | JSQuAD |
| :-- | :-- | :-- | :-- | :-- | :-- |
| tsubaki-10b-instruction-sft | 79.04 | 74.35 | 65.65 | 96.06 | 80.09 |
| tsubaki-10b | 67.27 | 65.86 | 54.19 | 84.49 | 64.54 |
---
# How to use the model
~~~~python
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Kojima777/tsubaki-10b", use_fast=False)
model = AutoModelForCausalLM.from_pretrained("Kojima777/tsubaki-10b")
if torch.cuda.is_available():
model = model.to("cuda")
text = "吾輩は猫である。"
token_ids = tokenizer.encode(text, add_special_tokens=False, return_tensors="pt")
with torch.no_grad():
output_ids = model.generate(
token_ids.to(model.device),
max_new_tokens=100,
do_sample=True,
temperature=0.6,
top_p=0.9,
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)
~~~~
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# Licenese
[cc-by-nc-4.0](https://creativecommons.org/licenses/by-nc/4.0/) |