TinyLlama-1.1B-Chat-v1.0-GGUF
| Property | Value |
|---|---|
| Parameter Count | 1.1B |
| Model Type | Chat Model |
| License | Apache 2.0 |
| Architecture | Llama 2 |
What is TinyLlama-1.1B-Chat-v1.0-GGUF?
TinyLlama-1.1B-Chat-v1.0-GGUF is a compact, efficient language model that brings the power of Llama 2 architecture to resource-constrained environments. This GGUF version, quantized by TheBloke, offers various compression levels from 2-bit to 8-bit, making it highly adaptable for different hardware configurations.
Implementation Details
The model was initially trained on 3 trillion tokens and fine-tuned using the UltraChat dataset. It employs the same architecture and tokenizer as Llama 2, making it compatible with existing Llama-based applications. The GGUF format enables efficient inference on both CPU and GPU.
- Multiple quantization options (Q2_K to Q8_0)
- File sizes ranging from 0.48GB to 1.17GB
- Compatible with llama.cpp and various UI implementations
- Supports context length up to 2048 tokens
Core Capabilities
- Chat-based interactions using Zephyr prompt template
- Efficient resource utilization with various quantization options
- GPU acceleration support with layer offloading
- Integration with popular frameworks like LangChain
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its efficient balance between size and performance, offering Llama 2 architecture benefits in a compact 1.1B parameter package. The various GGUF quantizations make it highly versatile for different deployment scenarios.
Q: What are the recommended use cases?
The model is ideal for resource-constrained environments, edge devices, and applications requiring quick response times. It's particularly suitable for chat applications, text generation, and integration into larger systems through Python libraries like llama-cpp-python.
