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--- |
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license: cc-by-nc-sa-4.0 |
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language: |
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- 'no' |
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--- |
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Gnerative Pretrained Tranformer with 3 Billion parameters for Norwegian. The model is continue trained using NorGPT-3B model on a selective documents from the pretraining dataset, which includes news articles, parlamentary speech, books and govermental reports. |
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It belongs to NorGLM, a suite of pretrained Norwegian Generative Language Models. NorGLM can be used for non-commercial purposes. |
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## Run the Model |
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```python |
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import torch |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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model_id = "NorGLM/NorGPT-3B-continue" |
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tokenizer = AutoTokenizer.from_pretrained(model_id) |
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model = AutoModelForCausalLM.from_pretrained( |
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model_id, |
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device_map='auto', |
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torch_dtype=torch.bfloat16 |
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) |
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text = "Tom ønsket å gå på barene med venner" |
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inputs = tokenizer(text, return_tensors="pt") |
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outputs = model.generate(**inputs, max_new_tokens=20) |
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``` |
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## Citation Information |
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If you feel our work is helpful, please cite our paper: |
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``` |
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@article{liu2023nlebench+, |
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title={NLEBench+ NorGLM: A Comprehensive Empirical Analysis and Benchmark Dataset for Generative Language Models in Norwegian}, |
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author={Liu, Peng and Zhang, Lemei and Farup, Terje Nissen and Lauvrak, Even W and Ingvaldsen, Jon Espen and Eide, Simen and Gulla, Jon Atle and Yang, Zhirong}, |
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journal={arXiv preprint arXiv:2312.01314}, |
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year={2023} |
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} |
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``` |
