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README.md

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+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
+
+[Discord](https://discord.gg/pvy7H8DZMG)
+
+[Request more models](https://github.com/RichardErkhov/quant_request)
+
+
+NorLlama-3B - bnb 4bits
+- Model creator: https://huggingface.co/NorGLM/
+- Original model: https://huggingface.co/NorGLM/NorLlama-3B/
+
+
+
+
+Original model description:
+---
+license: cc-by-nc-sa-4.0
+language:
+- 'no'
+---
+
+Gnerative Pretrained Tranformer with 3 Billion parameters for Norwegian. NorLlama-3B is based on Llama architechture, and pretrained on [Tencent Pre-training Framework](https://github.com/Tencent/TencentPretrain)
+
+It belongs to NorGLM, a suite of pretrained Norwegian Generative Language Models. NorGLM can be used for non-commercial purposes.
+
+## Datasets
+All models in NorGLM are trained on 200G datasets, nearly 25B tokens, including Norwegian, Denish, Swedish, Germany and English.
+
+## Run the Model
+
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_id = "NorGLM/NorLlama-3B"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    device_map='auto',
+    torch_dtype=torch.bfloat16
+)
+
+text = "Tom ønsket å gå på barene med venner"
+inputs = tokenizer(text, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=20)
+```
+
+## Citation Information
+If you feel our work is helpful, please cite our paper:
+
+```
+@article{liu2023nlebench+,
+  title={NLEBench+ NorGLM: A Comprehensive Empirical Analysis and Benchmark Dataset for Generative Language Models in Norwegian},
+  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},
+  journal={arXiv preprint arXiv:2312.01314},
+  year={2023}
+}
+```
+