Model Overview
The sampluralis/llama-mid-qkvo is a 1 billion parameter language model, derived from a fine-tuning process applied to the gshasiri/llama3.2-1B-chatml base model. This fine-tuning was conducted using the TRL library, a framework specifically designed for Transformer Reinforcement Learning.
Key Capabilities
- Conversational Text Generation: Optimized for generating responses in a chat-like format, making it suitable for interactive applications.
- Compact Size: With 1 billion parameters, it offers a balance between performance and computational efficiency, ideal for resource-constrained environments.
- Fine-tuned Performance: Leverages the SFT (Supervised Fine-Tuning) method to enhance its ability to follow instructions and generate coherent text.
Training Details
The model's training procedure utilized SFT, with progress and metrics tracked via Weights & Biases. The development environment included specific versions of key libraries:
- TRL: 0.28.0
- Transformers: 4.57.6
- Pytorch: 2.6.0+cu126
- Datasets: 4.6.0
- Tokenizers: 0.22.2
Use Cases
This model is well-suited for applications requiring a small, efficient language model capable of generating human-like text in response to prompts, particularly in conversational AI, chatbots, and interactive content generation where a smaller footprint is advantageous.