趋近智
参数
70B
上下文长度
8.192K
模态
Text
架构
Dense
许可证
Meta Llama 3 Community License
发布日期
18 Apr 2024
知识截止
Dec 2023
注意力结构
Grouped-Query Attention
隐藏维度大小
8192
层数
80
注意力头
64
键值头
8
激活函数
-
归一化
-
位置嵌入
ROPE
不同量化方法和上下文大小的显存要求
Meta Llama 3 70B is a 70-billion-parameter, decoder-only transformer language model developed by Meta. Released in April 2024, it is provided in both pre-trained and instruction-fine-tuned variants. The instruction-tuned model is specifically optimized for dialogue and assistant-style interactions, supporting a wide array of natural language understanding and generation tasks. These include conversational AI applications, creative content generation, code generation, text summarization, classification, and complex reasoning challenges. The model is made available for both commercial and research applications under the Meta Llama 3 Community License.
Architecturally, Llama 3 70B employs a standard decoder-only transformer design. A key innovation is its tokenizer, which features a vocabulary size of 128,000 tokens, contributing to enhanced language encoding efficiency and optimized inference. To further improve inference scalability and speed, the model integrates Grouped Query Attention (GQA). This attention mechanism is applied across both the 8B and 70B parameter versions of Llama 3. Initial training of the model was conducted on sequences up to 8,192 tokens. For the instruction-tuned variants, supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) were utilized to align model outputs with human preferences for helpfulness and safety.
The Llama 3 70B model is engineered for general-purpose applications, serving as a foundational technology that can be further adapted for domain-specific tasks. Its capabilities extend to powering advanced assistant functionalities, as demonstrated by its integration into Meta AI applications across various platforms. The model's design focuses on enabling developers to build diverse generative AI applications, from complex coding assistants to long-form text summarization tools, while offering control and flexibility in deployment environments, including on-premise, cloud, and local setups.
Meta's Llama 3 is a series of large language models utilizing a decoder-only transformer architecture. It incorporates a 128K token vocabulary and Grouped Query Attention for efficient processing. Models are trained on substantial public datasets, supporting various parameter scales and extended context lengths.
排名适用于本地LLM。
排名
#29
基准 | 分数 | 排名 |
---|---|---|
Refactoring Aider Refactoring | 0.49 | 10 |
Coding Aider Coding | 0.49 | 13 |