Llama 3 pre-training
×Stage · Llama 3 (April 2024)
Llama 3 was pretrained on over 15 trillion tokens of publicly available data, on sequences of 8,192 tokens with a mask that keeps attention within a document.
- Tokens
- over 15T
- Context
- 8,192, attention within a document
- Compute
- 1.3M and 6.4M GPU hours
Not disclosed Objective · Learning rate · Batch
Architecture at this stageLlama 3: the same shapes at 8B and 70B as Llama 3.1, a context of 8,192 and unscaled RoPE.
All settings3
- Tokens
- Over 15T (“15T+”), publicly available data
- Context
- Sequences of 8,192 tokens, with a mask so that self-attention does not cross document boundaries
- Compute
- 1.3M GPU hours for 8B, 6.4M for 70B
Sources5
- MODEL_CARD.md, lines 28–62Tokens
- MODEL_CARD.md, line 139Tokens
- meta-llama-3-post.htmlTokens, Context
- MODEL_CARD.md, line 13Context
- MODEL_CARD.md, lines 103–113Compute