SEA-LION-7B
Parameters
7.1B
Context Length
2K
Modality
Text
Architecture
Dense
License
Apache-2.0
Release Date
1 Dec 2023
Knowledge Cutoff
Sep 2023
System Requirements
VRAM requirements for different quantization methods and context sizes
1,024 tokens
Consumer
1x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
2,048 tokens
Consumer
1x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
No evaluation benchmarks for SEA-LION-7B available.
Rankings
Overall Rank
-
Coding Rank
-
About SEA-LION-7B
SEA-LION-7B (Southeast Asian Languages In One Network) is a 7.1 billion parameter decoder-only transformer model developed by AI Singapore to address the linguistic and cultural specificities of the Southeast Asian region. Built on the MosaicML Pretrained Transformer (MPT) architecture, the model is trained from scratch on a massive 980 billion token corpus. This training set is uniquely balanced, featuring significant representation for 11 regional languages including Indonesian, Malay, Thai, Vietnamese, Filipino, Tamil, Burmese, Khmer, and Lao, alongside English and Chinese, ensuring the model captures regional nuances often overlooked by Western-centric LLMs.
Technically, SEA-LION-7B diverges from standard MPT configurations by utilizing absolute learned positional embeddings rather than ALiBi, which provides a stable foundation for its 2,048-token context window. The architecture consists of 32 transformer layers with a hidden dimension of 4096 and 32 attention heads. It employs Low-Precision LayerNorm for normalization and uses the GeLU (Gaussian Error Linear Unit) activation function. A critical innovation is the SEABPETokenizer, a custom Byte-Pair Encoding tokenizer with a 256,000-token vocabulary specifically optimized to reduce the token-to-word ratio for Southeast Asian scripts, thereby improving inference efficiency and comprehension.
Designed for research and regional application deployment, SEA-LION-7B serves as a base for specialized natural language understanding and generation tasks. Its performance characteristics are tailored for multilingual translation, sentiment analysis, and culturally aware text generation within the ASEAN context. The model's open-weights release under the MIT license encourages community-driven fine-tuning and adaptation for specific regional industrial use cases while maintaining a transparent and accessible framework for researchers and developers.
Technical Specifications
Attention
Attention Structure
Multi-Head Attention
Attention Heads
32
Key-Value Heads
32
Attention Head Dimension
128
Position Embedding
Absolute Position Embedding
RoPE Theta
-
Sliding Window Attention
No
Sliding Window Size
-
Sliding Window Ratio
-
Linear Attention
-
Linear Attention Ratio
-
Normalization
Layer Normalization
Activation Function
GELU
Dimensions
Hidden Dimension Size
4,096
Number of Layers
32
FFN Intermediate Size (Dense)
16,384
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
256,000
About SEA-LION
Southeast Asian Languages In One Network (SEA-LION) is a family of language models developed by AI Singapore for Southeast Asian languages. The models support English, Indonesian, Malay, Thai, Vietnamese, Tagalog, Burmese, Khmer, Lao, Tamil, and Chinese. It focuses on regional linguistic patterns and is available in base and instruction-tuned variants.