Bitnet B1 58 Xl
BitNet b1.58 3B is a 1-bit quantized large language model trained on 100 billion tokens from the RedPajama dataset, significantly reducing computational resource requirements while maintaining performance.
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Release Time : 3/29/2024
Model Overview
This model is a reproduction implementation of the BitNet b1.58 paper, utilizing 1.58-bit quantization technology to provide an efficient language model solution.
Model Features
1-bit quantization
Utilizes 1.58-bit quantization technology, significantly reducing model storage and computational demands.
Efficient training
Optimizes the training process with two-stage learning rate adjustment and weight decay.
Performance close to full-precision models
At the 3B parameter scale, performance is close to that of FP16 full-precision models.
Model Capabilities
Text generation
Language understanding
Zero-shot learning
Use Cases
Natural Language Processing
Question answering systems
Can be used to build efficient question answering systems
Performs well on benchmarks like ARC
Text generation
Suitable for various text generation tasks
Perplexity (PPL) performance is close to full-precision models
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