Llama-3-8B-Instruct-Gradient-4194k
| Property | Value |
|---|---|
| Parameter Count | 8.03B |
| Context Length | 4194k tokens |
| License | Llama3 |
| Base Model | Meta Llama-3 8B |
| Training Tokens | 201M tokens |
What is Llama-3-8B-Instruct-Gradient-4194k?
This model is an enhanced version of Meta's Llama-3 8B that extends the context length from 8k to 4194k tokens. Developed by Gradient AI with compute sponsorship from Crusoe Energy, it demonstrates how state-of-the-art LLMs can be adapted for extremely long context processing through minimal but targeted training.
Implementation Details
The model uses progressive training across increasing context lengths (65K → 4191K) with NTK-aware interpolation following specific scaling laws. The training process involved only 201M tokens, approximately 0.01% of Llama-3's original pre-training data, yet achieved significant improvements in long-context handling.
- Employs EasyContext Blockwise RingAttention library for efficient training
- Custom network topology for optimized GPU cluster utilization
- Trained using NVIDIA L40S GPUs across multiple stages
- Uses BF16 precision for optimal performance
Core Capabilities
- Handles context lengths up to 4194k tokens
- Maintains base Llama-3 instruction-following abilities
- Optimized for long-form content processing
- Efficient memory usage through advanced attention mechanisms
Frequently Asked Questions
Q: What makes this model unique?
The model's ability to handle extremely long contexts (4194k tokens) while requiring minimal training data sets it apart. It achieves this through careful progressive training and optimized RoPE theta scheduling.
Q: What are the recommended use cases?
This model is ideal for tasks requiring processing of very long documents, such as document analysis, long-form content generation, and complex multi-document reasoning tasks. It's particularly suitable for applications needing extended context understanding while maintaining instruction-following capabilities.
