llama2-13b-orca-8k-3319
| Property | Value |
|---|---|
| Base Model | Llama-2-13b |
| Context Length | 8192 tokens |
| License | Llama 2 Community License |
| Paper | ORCA Paper |
| Training Steps | 3319 |
What is llama2-13b-orca-8k-3319?
This is an advanced fine-tuned version of Meta's Llama2 13B model, specifically optimized for handling long-form conversations with an extended context window of 8K tokens. The model leverages linear scaling of RoPE (Rotary Position Embeddings) and combines multiple high-quality datasets for enhanced performance.
Implementation Details
The model implements several technical innovations, including RoPE scaling for extended context handling and utilizes a multi-dataset training approach combining Orca-Chat/Dolphin, RedPajama1T, and FanFics datasets. It requires Huggingface Transformers 4.31.0 or higher and supports fp16 precision for efficient inference.
- Trained with 8192 token context window using linear RoPE scaling
- Combines three major datasets for comprehensive language understanding
- Implements 15 different system message templates for varied task handling
- Uses gradient checkpointing and flash attention for efficient training
Core Capabilities
- Extended context processing up to 8K tokens
- Specialized in detailed, long-form responses
- Multi-turn conversation support with structured prompt format
- Optimized for both task completion and general dialogue
Frequently Asked Questions
Q: What makes this model unique?
The model's unique feature is its combination of extended context length (8K tokens) with specialized training on long-form conversations, making it particularly effective for detailed, multi-turn interactions while maintaining the core capabilities of Llama2.
Q: What are the recommended use cases?
This model excels in scenarios requiring detailed explanations, long-form content generation, multi-turn conversations, and tasks requiring extended context understanding. It's particularly suitable for educational content, technical explanations, and complex dialogue scenarios.
