TinyLlama-1.1B-Chat-v0.1
| Property | Value |
|---|---|
| Parameter Count | 1.1B parameters |
| License | Apache 2.0 |
| Training Data | SlimPajama-627B, starcoderdata, openassistant-guanaco |
| Architecture | Llama 2-based |
What is TinyLlama-1.1B-Chat-v0.1?
TinyLlama-1.1B-Chat-v0.1 is a compact language model that aims to bring the power of Llama 2 architecture to resource-constrained environments. This chat-specific version is fine-tuned on the openassistant-guanaco dataset, making it particularly suitable for conversational AI applications.
Implementation Details
The model utilizes the same architecture and tokenizer as Llama 2, allowing seamless integration with existing Llama-based projects. It was trained using 16 A100-40G GPUs and optimized to process 3 trillion tokens within 90 days.
- Compatible with transformers>=4.31
- Supports both CPU and GPU inference
- Implements efficient F32 tensor operations
- Utilizes advanced text generation parameters including top-k and top-p sampling
Core Capabilities
- Chat-based text generation
- Efficient deployment in memory-constrained environments
- Plugin compatibility with Llama ecosystem
- Multi-turn conversation support
Frequently Asked Questions
Q: What makes this model unique?
TinyLlama stands out for its efficient architecture that maintains Llama 2 compatibility while requiring significantly fewer computational resources. Its 1.1B parameter size makes it accessible for deployment on consumer hardware.
Q: What are the recommended use cases?
The model is ideal for applications requiring lightweight chatbot functionality, edge device deployment, and scenarios where computational resources are limited but Llama 2-like capabilities are desired.
