shubhamgupta7217/MyGemmaNPC
MyGemmaNPC by shubhamgupta7217 is a 0.3 billion parameter instruction-tuned causal language model, fine-tuned from google/gemma-3-270m-it. This model leverages a 32768 token context length and is specifically optimized for conversational AI tasks, making it suitable for generating human-like responses in interactive applications. Its small size and fine-tuned nature allow for efficient deployment in scenarios requiring responsive, instruction-following capabilities.
Loading preview...
Model Overview
shubhamgupta7217/MyGemmaNPC is a 0.3 billion parameter instruction-tuned language model, built upon the google/gemma-3-270m-it architecture. This model has been fine-tuned using the TRL library to enhance its ability to follow instructions and generate coherent text.
Key Capabilities
- Instruction Following: Optimized for understanding and responding to user instructions, making it suitable for interactive applications.
- Text Generation: Capable of generating human-like text based on given prompts.
- Efficient Deployment: Its relatively small size (0.3B parameters) allows for more efficient inference compared to larger models, while still maintaining a substantial 32768 token context length.
Training Details
The model was trained using the Supervised Fine-Tuning (SFT) method. The training utilized specific versions of key frameworks:
- TRL: 1.7.0
- Transformers: 5.12.1
- Pytorch: 2.11.0+cu128
- Datasets: 5.0.0
- Tokenizers: 0.22.2
Use Cases
This model is well-suited for applications requiring a compact yet capable language model for tasks such as:
- Chatbots and conversational agents
- Generating responses in interactive scenarios
- Prototyping and development where resource efficiency is important