MPT-7B-Chat
| Property | Value |
|---|---|
| Parameter Count | 6.7B |
| License | CC-By-NC-SA-4.0 (non-commercial) |
| Architecture | Modified decoder-only transformer |
| Context Length | 2048 tokens (expandable) |
| Training Duration | 9.5 days |
What is MPT-7B-Chat?
MPT-7B-Chat is an advanced language model developed by MosaicML, specifically designed for dialogue generation. It's built upon the base MPT-7B model through fine-tuning on multiple high-quality conversation datasets including ShareGPT-Vicuna, HC3, Alpaca, HH-RLHF, and Evol-Instruct.
Implementation Details
The model implements several cutting-edge technical innovations in transformer architecture:
- FlashAttention for improved computational efficiency
- ALiBi (Attention with Linear Biases) replacing traditional positional embeddings
- Bias-free architecture design
- 32 layers with 32 attention heads
- 4096 dimensional model representations
Core Capabilities
- High-quality dialogue generation and chat interactions
- Expandable context length beyond training window (2048 tokens)
- Efficient inference with triton implementation support
- Compatible with popular frameworks like PyTorch and Hugging Face Transformers
Frequently Asked Questions
Q: What makes this model unique?
The model combines state-of-the-art architectural innovations like FlashAttention and ALiBi with extensive fine-tuning on diverse dialogue datasets, making it particularly effective for chat applications while maintaining efficient computation.
Q: What are the recommended use cases?
MPT-7B-Chat is ideal for building chatbots, dialogue systems, and interactive AI applications. However, due to its CC-By-NC-SA-4.0 license, it's restricted to non-commercial use only.
