Sahabat-AI-Llama3-8B-Instruct
Parameters
8B
Context Length
8K
Modality
Text
Architecture
Dense
License
Llama-3.1-Community
Release Date
14 Nov 2024
Knowledge Cutoff
Mar 2023
API Pricing (per 1M)
Self-hosted only
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
8,192 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 Sahabat-AI-Llama3-8B-Instruct available.
Rankings
Overall Rank
-
Coding Rank
-
About Sahabat-AI-Llama3-8B-Instruct
Sahabat-AI-Llama3-8B-Instruct is an Indonesian instruction-tuned model developed by GoTo and Indosat on Llama 3 for localized customer support and text synthesis. It incorporates regional cultural context across formal and colloquial language.
Technical Specifications
Attention
Attention Structure
Multi-Head Attention
Attention Heads
32
Key-Value Heads
8
Attention Head Dimension
128
Position Embedding
Absolute Position Embedding
RoPE Theta
500,000
Sliding Window Attention
No
Sliding Window Size
-
Sliding Window Ratio
-
Linear Attention
-
Linear Attention Ratio
-
Normalization
RMS Normalization
Activation Function
SwigLU
Dimensions
Hidden Dimension Size
4,096
Number of Layers
32
FFN Intermediate Size (Dense)
14,336
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
128,256
About Sahabat-AI
Sahabat-AI is an Indonesian language model family co-initiated by GoTo and Indosat Ooredoo Hutchison. Developed with AI Singapore and NVIDIA, it is a collection of models (based on Gemma 2 and Llama 3) specifically optimized for Bahasa Indonesia and regional languages like Javanese and Sundanese.