SEA-LION-7B
Parameters
7.1B
Context Length
2K
Modality
Text
Architecture
Dense
KV Cache Rate
512 KB/tok
License
Apache-2.0
Release Date
1 Dec 2023
Knowledge Cutoff
Sep 2023
API Pricing (per 1M)
Self-hosted only
Hardware & System Requirements
Precision
Context
Workload Memory: 6.81 GB
INT4 · 2048 context
Base Weights: 3.31 GB
KV Cache: 1.00 GB
Runtime & Graphs: 2.50 GB
Minimum Required Hardware
1x NVIDIA L4 24GB
6.8 / 21.6 GB usable
1x RTX 3060 12GB
6.8 / 10.8 GB usable
Apple M4 24GB
6.8 / 18.0 GB usable
Determine requirements for your specific workload:
Open in VRAM Calculator
Runtime requirements
Checkpoint format
FP16
CUDA
>= 11.8
PyTorch
>= 2.1
Transformers
>= 4.34.1
| Architecture | Precision | Attention kernel |
|---|---|---|
Blackwell, Hopper | Native FP16 | FlashAttention-3 |
Ada Lovelace, Ampere | Native FP16 | FlashAttention-2 |
Architecture Diagram
Evaluation Benchmarks
No evaluation benchmarks for SEA-LION-7B available.
Rankings
Overall Rank
-
Coding Rank
-
About SEA-LION-7B
SEA-LION-7B is an open foundation model developed by AI Singapore specifically pretrained on 11 Southeast Asian languages and English. It utilizes a custom 256K-token SEABPETokenizer for culturally nuanced and efficient regional text generation.
Specifications
Attention
Attention Structure
Multi-Head Attention
Attention Heads
32
Key-Value Heads
32
Attention Head Dimension
128
Position Embedding
Absolute Position Embedding
Normalization
Layer Normalization
Activation Function
GELU
Dimensions
Base Precision
FP16
Hidden Dimension Size
4,096
Number of Layers
32
FFN Intermediate Size (Dense)
16,384
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.