SEA-LION-7B-Instruct
Parameters
7.1B
Context Length
2K
Modality
Text
Architecture
Dense
KV Cache Rate
512 KB/tok
License
Apache-2.0
Release Date
1 Feb 2024
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
>= 4.37.2
| Architecture | Precision | Attention kernel |
|---|---|---|
Blackwell, Hopper | Native FP16 | FlashAttention-3 |
Ada Lovelace, Ampere | Native FP16 | FlashAttention-2 |
Additional required packages
Install alongside standard runtime libraries:
pip install flash_attn
Architecture Diagram
Evaluation Benchmarks
No evaluation benchmarks for SEA-LION-7B-Instruct available.
Rankings
Overall Rank
-
Coding Rank
-
About SEA-LION-7B-Instruct
SEA-LION-7B-Instruct is an instruction-tuned model from AI Singapore optimized for regional question answering, translation, and localized agents across ASEAN languages. It features Grouped-Query Attention and culturally aligned instruction tuning.
Specifications
Attention
Attention Structure
Multi-Head Attention
Attention Heads
32
Key-Value Heads
32
Attention Head Dimension
128
Position Embedding
Absolute Position Embedding
Normalization
RMS Normalization
Activation Function
SwigLU
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.