Hugging Face Overview
Model Overview
The Naomarik/pirate-gemma3-1b is a 1 billion parameter instruction-tuned language model, built upon Google's gemma-3-1b-it architecture. This model has been fine-tuned using Supervised Fine-Tuning (SFT) with the TRL library, enhancing its ability to follow instructions and generate coherent text.
Key Capabilities
- Instruction Following: Inherits and refines the instruction-tuned capabilities of its base model, making it suitable for various prompt-based tasks.
- Text Generation: Capable of generating diverse text outputs based on user prompts, including responses to questions and conversational turns.
- Context Length: Supports a substantial context window of 32768 tokens, allowing for processing and generating longer sequences of text.
Training Details
The model's training procedure involved SFT, utilizing specific versions of popular machine learning frameworks:
- PEFT: 0.18.1
- TRL: 0.26.2
- Transformers: 4.57.5
- Pytorch: 2.9.1+rocm6.3
- Datasets: 4.4.2
- Tokenizers: 0.22.2
Use Cases
This model is well-suited for applications requiring a compact yet capable instruction-following language model, such as:
- General-purpose chatbots
- Question answering systems
- Content generation based on specific instructions