Llama3-8B-1.58-100B-tokens
| Property | Value |
|---|---|
| Parameter Count | 2.8B parameters |
| Model Type | Text Generation, Conversational |
| Architecture | BitNet 1.58b based on Llama-3 |
| Paper | The Era of 1-bit LLMs |
| Tensor Type | BF16, U8 |
What is Llama3-8B-1.58-100B-tokens?
This is a groundbreaking implementation of the Llama-3 architecture using extreme quantization through the BitNet 1.58b architecture. The model represents a significant advancement in efficient AI models, trained on 100 billion tokens from the FineWeb-edu dataset, achieving performance close to its full-precision counterpart while significantly reducing computational requirements.
Implementation Details
The model underwent extensive training, starting with a 10 billion token initialization followed by 45,000 additional training steps. It processes 2 million tokens per step, utilizing an optimized learning rate of 1e-5 for peak performance.
- Fine-tuned from Llama-3-8B-Instruct base model
- Implements BitNet 1.58b architecture for extreme quantization
- Trained on FineWeb-edu dataset
- Utilizes mixed precision with BF16 and U8 tensors
Core Capabilities
- Text generation and conversational tasks
- Efficient inference with reduced memory footprint
- Performance comparable to full-precision models in certain metrics
- Optimized for production deployment
Frequently Asked Questions
Q: What makes this model unique?
This model pioneers the use of 1.58-bit quantization while maintaining impressive performance, representing a significant breakthrough in model efficiency and deployment capabilities.
Q: What are the recommended use cases?
The model is particularly well-suited for text generation and conversational applications where computational resources are limited but high-quality output is required.
