Gemma 1 7B
Parameters
7B
Context Length
8K
Modality
Text
Architecture
Dense
License
Gemma Terms of Use
Release Date
21 Feb 2024
Knowledge Cutoff
-
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
Rank
#149
| Benchmark | Score | Rank |
|---|---|---|
General Text | 1182 | 167 |
Rankings
Overall Rank
#149
Coding Rank
-
About Gemma 1 7B
Gemma 1 7B is Google's foundational open-weights decoder-only transformer engineered for general text generation and reasoning. Trained on 6T tokens, it offers an efficient balance of capability and accessible deployment on local workstations.
Technical Specifications
Attention
Attention Structure
Multi-Head Attention
Attention Heads
32
Key-Value Heads
32
Attention Head Dimension
-
Position Embedding
ROPE
RoPE Theta
-
Sliding Window Attention
-
Sliding Window Size
-
Sliding Window Ratio
-
Linear Attention
-
Linear Attention Ratio
-
Normalization
RMS Normalization
Activation Function
-
Dimensions
Hidden Dimension Size
3,072
Number of Layers
28
FFN Intermediate Size (Dense)
-
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
-
About Gemma 1
Gemma 1 is a family of lightweight, decoder-only transformer models from Google, available in 2B and 7B parameter sizes. Designed for various text generation tasks, they incorporate rotary positional embeddings, shared input/output embeddings, GEGLU activation, and RMSNorm. The 2B model uses multi-query attention, while 7B uses multi-head attention.