StableLM-Tuned-Alpha-7B
| Property | Value |
|---|---|
| Parameter Count | 7 Billion |
| Model Type | Decoder-only Language Model |
| Architecture | NeoX-based Transformer |
| License | CC BY-NC-SA-4.0 |
| Developer | Stability AI |
What is stablelm-tuned-alpha-7b?
StableLM-Tuned-Alpha-7B is an advanced language model developed by Stability AI, specifically designed for chat and instruction-following tasks. Built on the NeoX transformer architecture, it features 6144 hidden dimensions across 16 layers with 48 attention heads, capable of processing sequences up to 4096 tokens. The model represents a significant advancement in open-source AI language models, combining powerful language understanding with ethical constraints.
Implementation Details
The model is implemented using the HuggingFace Transformers library and has been fine-tuned on a diverse set of high-quality datasets, including Alpaca, GPT4All, Anthropic HH, DataBricks Dolly, and ShareGPT Vicuna. The training process utilized mixed-precision (FP16) with AdamW optimizer, employing a learning rate of 2e-5 and a batch size of 128.
- Sophisticated architecture with 16 transformer layers and 48 attention heads
- 4096 token context window for comprehensive understanding
- Fine-tuned on multiple instruction-following and chat datasets
- Implements special tokens for system, user, and assistant interactions
Core Capabilities
- Natural language understanding and generation
- Chat-based interactions with proper context management
- Instruction following with safety constraints
- Poetry and creative writing abilities
- Question answering and information synthesis
Frequently Asked Questions
Q: What makes this model unique?
This model stands out through its combination of substantial parameter count (7B), carefully curated training datasets, and built-in safety measures. It's specifically designed to be helpful while refusing harmful requests, making it suitable for deployment in responsible AI applications.
Q: What are the recommended use cases?
The model is best suited for chat applications, instruction-following tasks, creative writing, and general language understanding tasks. It's particularly well-adapted for scenarios requiring both capability and ethical considerations, though it should not be used for commercial purposes due to its licensing.
