Mistral-7B-v0.1
Parameters
7.3B
Context Length
8K
Modality
Text
Architecture
Dense
License
Apache 2.0
Release Date
27 Sept 2023
Knowledge Cutoff
Aug 2021
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 Mistral-7B-v0.1 available.
Rankings
Overall Rank
-
Coding Rank
-
About Mistral-7B-v0.1
Mistral-7B-v0.1 is a 7.3 billion parameter large language model developed by Mistral AI, engineered for superior performance and computational efficiency in natural language processing tasks. Its design prioritizes efficient inference, making it suitable for practical deployment across various applications. The model is built upon a decoder-only transformer architecture, integrating several key innovations to optimize its operation.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
32
Key-Value Heads
8
Attention Head Dimension
-
Position Embedding
ROPE
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
SwigLU
Dimensions
Hidden Dimension Size
4,096
Number of Layers
32
FFN Intermediate Size (Dense)
14,336
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
32,000
About Mistral 7B
Mistral 7B, a 7.3 billion parameter model, utilizes a decoder-only transformer architecture. It features Sliding Window Attention and Grouped Query Attention for efficient long sequence processing. A Rolling Buffer Cache optimizes memory use, contributing to its design for efficient language processing.