Sahabat-AI-Gemma2-9B
Parameters
9.2B
Context Length
8K
Modality
Text
Architecture
Dense
License
Gemma-Community
Release Date
14 Nov 2024
Knowledge Cutoff
-
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-Gemma2-9B available.
Rankings
Overall Rank
-
Coding Rank
-
About Sahabat-AI-Gemma2-9B
Sahabat-AI-Gemma2-9B is an Indonesian sovereign foundation model developed by GoTo and Indosat on Gemma 2 for Indonesian and regional dialects. Pretrained on 50B local tokens, it delivers culturally nuanced translation and NLP capabilities.
Technical Specifications
Attention
Attention Structure
Multi-Head Attention
Attention Heads
16
Key-Value Heads
8
Attention Head Dimension
256
Position Embedding
Absolute Position Embedding
RoPE Theta
10,000
Sliding Window Attention
Yes
Sliding Window Size
4,096
Sliding Window Ratio
-
Linear Attention
-
Linear Attention Ratio
-
Normalization
RMS Normalization
Activation Function
Gated GELU
Dimensions
Hidden Dimension Size
3,584
Number of Layers
42
FFN Intermediate Size (Dense)
14,336
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
256,000
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.