The gradjitta/llama2-7b-merged-finnish-alpaca-buggy is a 7 billion parameter Llama 2-based language model fine-tuned for Finnish language tasks. This model was created by gradjitta by applying Supervised Fine-Tuning (SFT) on the datacrunch/finnish_alpaca dataset. It is specifically designed to generate responses in Finnish, making it suitable for applications requiring Finnish language understanding and generation.
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Overview
The gradjitta/llama2-7b-merged-finnish-alpaca-buggy is a 7 billion parameter language model derived from Meta's Llama 2 architecture. This model has undergone Supervised Fine-Tuning (SFT) using the datacrunch/finnish_alpaca dataset, specifically at a 500-step checkpoint of the training process. The fine-tuning was performed using the trl library's sft_trainer.py script.
Key Capabilities
- Finnish Language Generation: The primary capability of this model is generating responses in Finnish, as it was fine-tuned on a Finnish Alpaca dataset.
- Instruction Following: It is designed to follow instructions provided in a prompt format, similar to other instruction-tuned models.
Good For
- Finnish NLP Applications: Ideal for developers and researchers working on applications that require a language model with a strong understanding and generation capability in Finnish.
- Experimentation with SFT: Useful for those interested in experimenting with Supervised Fine-Tuning on Llama 2 models for specific language adaptations.
Usage Example
An example prompt provided for testing its Finnish response generation is:
"Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. ### Instruction: Anna kolme vinkkiä terveenä pysymiseen. ###Response:"