V4ldeLund/gemma-3-1b-it-faroese-experiment1
V4ldeLund/gemma-3-1b-it-faroese-experiment1 is a 1 billion parameter instruction-tuned causal language model, fine-tuned from Google's Gemma-3-1b-it architecture. This model is specifically trained using Supervised Fine-Tuning (SFT) with the TRL library, making it specialized for generating responses in Faroese. It is designed for conversational AI applications requiring interaction in the Faroese language.
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Model Overview
V4ldeLund/gemma-3-1b-it-faroese-experiment1 is a 1 billion parameter instruction-tuned language model, building upon the google/gemma-3-1b-it base. This model has undergone Supervised Fine-Tuning (SFT) using the TRL library, indicating a focus on instruction-following capabilities.
Key Characteristics
- Base Model: Fine-tuned from
google/gemma-3-1b-it. - Parameter Count: 1 billion parameters, offering a balance between performance and computational efficiency.
- Training Method: Utilizes Supervised Fine-Tuning (SFT) for instruction-following, as detailed in its Weights & Biases run.
- Frameworks: Developed with TRL 1.11.0, Transformers 5.16.1, PyTorch 2.13.0, Datasets 5.0.1, and Tokenizers 0.23.1.
Intended Use
This model is particularly suited for applications requiring instruction-tuned text generation, especially in contexts where the Faroese language is a primary focus due to its specialized fine-tuning. Developers can integrate it using the Hugging Face pipeline for text generation tasks.