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Sahabat-AI-Gemma2-9B-Instruct

Parameters

9.2B

Context Length

8K

Modality

Text

Architecture

Dense

License

Gemma-Community

Release Date

14 Nov 2024

Knowledge Cutoff

Mar 2024

API Pricing (per 1M)

Self-hosted only

System Requirements

VRAM requirements for different quantization methods and context sizes

1,024 tokens

21.19 GB VRAM

Consumer

1x RTX 4090

24GB VRAM

Datacenter

1x NVIDIA A100

80GB VRAM

Apple Silicon

1x Apple M3 Max

128GB VRAM

8,192 tokens

23.78 GB VRAM

Consumer

1x RTX 4090

24GB VRAM

Datacenter

1x NVIDIA A100

80GB VRAM

Apple Silicon

1x Apple M3 Max

128GB VRAM

Architecture Diagram

Input TokensToken EmbeddingPosition: AbsoluteHidden: 3.6k · Context: 8K · Vocab: 256kx 42 layersRMSNormPre-AttentionMulti-Head Attention16Q / 8KV heads · SW: 4.1kHead dim: 256+RMSNormPre-FFNFeed-Forward NetworkGated GELUIntermediate: 14.3k+Final RMSNormOutput Logits

Evaluation Benchmarks

No evaluation benchmarks for Sahabat-AI-Gemma2-9B-Instruct available.

Rankings

Overall Rank

-

Coding Rank

-

About Sahabat-AI-Gemma2-9B-Instruct

Sahabat-AI-Gemma2-9B-Instruct is an instruction-tuned Indonesian language model by GoTo, Indosat, and AI Singapore for enterprise chatbots and digital assistants. It excels in standard Bahasa Indonesia, Javanese, and Sundanese conversational tasks.

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.


Other Sahabat-AI Models
Sahabat-AI-Gemma2-9B-Instruct: Specifications and GPU VRAM Requirements