BELLE-7B-2M
| Property | Value |
|---|---|
| License | Apache 2.0 |
| Training Data Size | 2M samples |
| Languages | Chinese, English |
| Framework | PyTorch |
What is BELLE-7B-2M?
BELLE-7B-2M is an advanced language model based on Bloomz-7b1-mt, fine-tuned on 2 million Chinese instructions combined with 50,000 English samples from Stanford-Alpaca. This model represents the largest training dataset variant in the BELLE series, designed to excel at both Chinese instruction understanding and response generation.
Implementation Details
The model was trained using carefully selected hyperparameters including a batch size of 64, learning rate of 3e-6, and 3 epochs with linear learning rate scheduling. The training process incorporated weight decay of 0.001 and a warmup rate of 0.1 to ensure optimal performance.
- Comprehensive bilingual capability in Chinese and English
- Advanced text generation and understanding abilities
- Flexible deployment options with PyTorch integration
Core Capabilities
- Multilingual text generation and translation
- Sentiment analysis and classification
- Creative writing and content generation
- Code generation and explanation
- Dialogue generation and conversation
Frequently Asked Questions
Q: What makes this model unique?
BELLE-7B-2M stands out for its extensive training on 2 million Chinese instructions, making it particularly effective for Chinese language tasks while maintaining strong English capabilities. It's part of a systematic series of models trained on increasingly large datasets.
Q: What are the recommended use cases?
The model excels in various applications including text generation, translation, sentiment analysis, and creative writing. However, it's important to note that it's intended for research purposes only and should not be used for commercial applications.
