b1n1yam/addisAI_Finetune
The b1n1yam/addisAI_Finetune model is a 0.3 billion parameter instruction-tuned causal language model, fine-tuned from Google's Gemma-3-270m-it architecture. It was trained using the TRL framework to enhance its conversational capabilities. This model is optimized for general text generation tasks, particularly in response to user prompts, leveraging its compact size for efficient deployment.
Loading preview...
Model Overview
The b1n1yam/addisAI_Finetune model is a compact, instruction-tuned language model based on the google/gemma-3-270m-it architecture. With 0.3 billion parameters and a context length of 32768 tokens, it is designed for efficient text generation.
Key Capabilities
- Instruction Following: Fine-tuned to respond effectively to user prompts and instructions.
- Text Generation: Capable of generating coherent and contextually relevant text.
- Efficient Deployment: Its small parameter count makes it suitable for environments where computational resources are limited.
Training Details
This model was fine-tuned using the TRL (Transformer Reinforcement Learning) library, specifically employing Supervised Fine-Tuning (SFT) techniques. The training process utilized TRL version 0.21.0, Transformers 4.55.2, and Pytorch 2.8.0+cu126.
Good For
- Conversational AI: Generating responses in interactive applications.
- Prototyping: Quickly testing language model capabilities in resource-constrained settings.
- Educational Purposes: Understanding fine-tuning processes on a smaller, manageable model.