TinyLlama-1.1B-Chat-v1.0
| Property | Value |
|---|---|
| Parameter Count | 1.1B |
| License | Apache 2.0 |
| Tensor Type | BF16 |
| Training Data | SlimPajama-627B, StarCoder, UltraChat, UltraFeedback |
What is TinyLlama-1.1B-Chat-v1.0?
TinyLlama-1.1B-Chat-v1.0 is a compact yet powerful language model that represents a significant achievement in efficient AI design. Built on the same architecture as Llama 2, this model was trained on 3 trillion tokens over 90 days using 16 A100-40G GPUs. It's specifically optimized for chat applications while maintaining a small computational footprint.
Implementation Details
The model implements the Llama 2 architecture and tokenizer, making it compatible with existing Llama-based projects. It's fine-tuned using HuggingFace's Zephyr training recipe, incorporating UltraChat for dialogue generation and UltraFeedback for alignment through DPO training.
- Leverages BF16 tensor type for efficient computation
- Requires transformers >= 4.34 for implementation
- Supports automated device mapping for optimal resource utilization
- Implements chat templating for structured conversations
Core Capabilities
- Natural language conversation and dialogue generation
- Code generation and assistance
- Customizable conversation styling through system prompts
- Efficient deployment in resource-constrained environments
Frequently Asked Questions
Q: What makes this model unique?
Its combination of compact size (1.1B parameters) with extensive training (3T tokens) makes it uniquely efficient for deployment in applications with limited computational resources while maintaining strong performance.
Q: What are the recommended use cases?
The model is ideal for chat applications, code assistance, and general text generation tasks where resource efficiency is crucial. It's particularly suitable for applications requiring direct deployment on less powerful hardware.
