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Llama 3.1 70B

Parameters

70B

Context Length

128K

Modality

Text

Architecture

Dense

License

Llama 3.1 Community License Agreement

Release Date

23 Jul 2024

Knowledge Cutoff

Dec 2023

Technical Specifications

Attention Structure

Grouped-Query Attention

Hidden Dimension Size

8192

Number of Layers

80

Attention Heads

64

Key-Value Heads

8

Activation Function

-

Normalization

-

Position Embedding

ROPE

System Requirements

VRAM requirements for different quantization methods and context sizes

Llama 3.1 70B

Llama 3.1 70B is a large language model developed by Meta, designed to address a wide array of natural language processing tasks. This model variant builds upon its predecessors by offering enhanced capabilities across various applications. Its primary purpose includes facilitating content generation, powering conversational AI systems, performing sentiment analysis, and supporting code generation. The model is structured to be suitable for deployment in both research and enterprise environments, providing a robust foundation for diverse AI-native applications.

Architecturally, Llama 3.1 70B employs an optimized dense Transformer network. A significant technical advancement in this iteration is the expansion of its context length to 128,000 tokens, representing a substantial increase over previous Llama 3 models. This enables the model to process and generate coherent responses from extensive textual inputs, supporting advanced use cases requiring long-form context understanding. Furthermore, Llama 3.1 70B incorporates enhanced multilingual capabilities, enabling it to operate effectively in several languages beyond English, including German, French, Italian, Portuguese, Hindi, Spanish, and Thai. The model's training incorporates advanced techniques such as supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF), which contribute to its capacity for instruction following and contextual relevance.

In terms of performance characteristics and use cases, Llama 3.1 70B is engineered for high performance in large-scale AI applications. Its expanded context window and multilingual support make it suitable for tasks such as comprehensive text summarization, development of sophisticated multilingual conversational agents, and creation of coding assistants. The model supports a variety of common natural language generation tasks, making it a versatile tool for developers and organizations aiming to integrate cutting-edge AI technology into their workflows.

About Llama 3.1

Llama 3.1 is Meta's advanced large language model family, building upon Llama 3. It features an optimized decoder-only transformer architecture, available in 8B, 70B, and 405B parameter versions. Significant enhancements include an expanded 128K token context window and improved multilingual capabilities across eight languages, refined through data and post-training procedures.


Other Llama 3.1 Models

Evaluation Benchmarks

Ranking is for Local LLMs.

Rank

#31

BenchmarkScoreRank

0.95

🥉

3

General Knowledge

MMLU

0.80

5

0.59

7

0.92

8

0.59

11

0.6

13

Professional Knowledge

MMLU Pro

0.66

15

0.54

17

Graduate-Level QA

GPQA

0.42

23

0.30

24

0.33

27

0.20

28

Rankings

Overall Rank

#31

Coding Rank

#24

GPU Requirements

Full Calculator

Choose the quantization method for model weights

Context Size: 1,024 tokens

1k
63k
125k

VRAM Required:

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