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A model fine-tuned on Norwegian prompt/response pairs relevant to the curriculum in radation physics, radation protection and radiological technology for dentistry and dental hygiene students. It is an experimental model not yet stable enough to use in production.
Model Details
Model Description
Model
The base model used is the Meta Llama 13B model (meta-llama/Llama-2-13b-hf).
Data
A dataset of prompt/response pairs about radiation protection, radiation physics, radiation biology and radiological technology as the apply in dental clinics was used to fine-tune the model. The dataset is in Norwegian and the model is fine-tuned to answer in Norwegian.
Training
The model was trained on 6.2k prompt/response pairs from the dataset meta-llama/Llama-2-13b-hf for 6 epochs on a Google Colag notebook with an A100 GPU.
The Unsloth library was used to train the model on a single A100 GPU.
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
Developed by: Gerald Torgersen
Model type: Chat model fine-tuned
Language(s) (NLP): Norwegian
License: Llama 2
Finetuned from model [meta-llama/Llama-2-13b-hf]:
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Uses
For teaching and learning.
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Bias, Risks, and Limitations
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Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
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Training Details
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Training Procedure
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Evaluation
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Summary
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Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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