jvjmoura/queensland-ai-gemma3-fine-tuned-live
The jvjmoura/queensland-ai-gemma3-fine-tuned-live model is a 0.3 billion parameter instruction-tuned Gemma-3 variant, fine-tuned by jvjmoura using TRL. This model is based on google/gemma-3-270m-it and specializes in text generation tasks, particularly conversational responses. With a context length of 32768 tokens, it is optimized for generating coherent and relevant text based on user prompts.
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Model Overview
This model, jvjmoura/queensland-ai-gemma3-fine-tuned-live, is a fine-tuned version of Google's gemma-3-270m-it model. It has been specifically trained using the TRL library for supervised fine-tuning (SFT) to enhance its text generation capabilities.
Key Capabilities
- Instruction-following: Designed to generate responses based on user instructions, making it suitable for interactive applications.
- Text Generation: Excels at producing coherent and contextually relevant text, as demonstrated by its ability to answer open-ended questions.
- Gemma-3 Architecture: Leverages the efficient and capable Gemma-3 architecture, providing a solid foundation for its performance.
Training Details
The model underwent a supervised fine-tuning (SFT) process. The training utilized the following framework versions:
- TRL: 1.6.0
- Transformers: 5.12.0
- Pytorch: 2.11.0+cu128
- Datasets: 5.0.0
- Tokenizers: 0.22.2
Good For
- Conversational AI: Generating human-like responses in chatbots or interactive agents.
- Creative Writing Prompts: Assisting with creative text generation tasks.
- Question Answering: Providing detailed answers to open-ended questions.
This model offers a compact yet capable solution for various text generation needs, building upon the robust Gemma-3 base.