This is a 3B-parameter decoder-only language model with a focus on maximizing Japanese language modeling performance and Japanese downstream task performance.
We conducted continued pretraining using Japanese data on the English language model,
StableLM-3B-4E1T
, to transfer the model's knowledge and capabilities to Japanese.
The model is a decoder-only transformer similar to the LLaMA (
Touvron et al., 2023
) architecture with the following modifications:
Parameters
Hidden Size
Layers
Heads
Sequence Length
2,795,443,200
2560
32
32
4096
Position Embeddings
: Rotary Position Embeddings (
Su et al., 2021
) applied to the first 25% of head embedding dimensions for improved throughput following
Black et al. (2022)
.
The model is intended to be used by all individuals as a foundational model for application-specific fine-tuning without strict limitations on commercial use.
Limitations and bias
The pre-training dataset may have contained offensive or inappropriate content even after applying data cleansing filters which can be reflected in the model-generated text. We recommend users exercise reasonable caution when using these models in production systems. Do not use the model for any applications that may cause harm or distress to individuals or groups.
We are grateful for the contributions of the EleutherAI Polyglot-JA team in helping us to collect a large amount of pre-training data in Japanese. Polyglot-JA members includes Hyunwoong Ko (Project Lead), Fujiki Nakamura (originally started this project when he commited to the Polyglot team), Yunho Mo, Minji Jung, KeunSeok Im, and Su-Kyeong Jang.
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