Llama-4-Scout-17B-16E-Instruct-unsloth-bnb-8bit
| Property | Value |
|---|---|
| Base Model | Llama 4 Scout |
| Parameters | 17B activated (109B total) |
| Context Length | 10M tokens |
| Training Data | ~40T tokens |
| Knowledge Cutoff | August 2024 |
| License | Llama 4 Community License |
What is Llama-4-Scout-17B-16E-Instruct-unsloth-bnb-8bit?
This is an optimized version of Meta's Llama 4 Scout model, featuring Unsloth's Dynamic Quants for selective 8-bit quantization. The model represents a significant advancement in the Llama ecosystem, implementing a mixture-of-experts (MoE) architecture with 16 experts for efficient performance in both text and image understanding tasks.
Implementation Details
The model utilizes a sophisticated architecture combining MoE with early fusion for native multimodality. It's been optimized using Unsloth's quantization techniques to maintain high accuracy while reducing computational requirements, making it deployable on standard hardware.
- Selective 8-bit quantization for optimal performance
- Support for 12 languages including Arabic, English, French, and others
- 10M token context window
- Native multimodal capabilities for text and image processing
Core Capabilities
- Multimodal understanding with support for up to 5 input images
- Advanced visual reasoning and image captioning
- Multilingual text generation and comprehension
- Code generation and analysis
- Long-context processing
Frequently Asked Questions
Q: What makes this model unique?
The model combines Meta's advanced Llama 4 architecture with Unsloth's optimization techniques, offering state-of-the-art performance in a more efficient package. The 16-expert MoE architecture and 8-bit quantization make it particularly suitable for practical deployments while maintaining high accuracy.
Q: What are the recommended use cases?
The model excels in assistant-like chat applications, visual reasoning tasks, multilingual text generation, and code-related tasks. It's particularly well-suited for commercial applications requiring both text and image understanding, with strong performance in document analysis and chart interpretation.
