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 - GGUF - Model creator: https://huggingface.co/NorGLM/ - Original model: https://huggingface.co/NorGLM/NorLlama-3B/ | Name | Quant method | Size | | ---- | ---- | ---- | | [NorLlama-3B.Q2_K.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.Q2_K.gguf) | Q2_K | 2.51GB | | [NorLlama-3B.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.IQ3_XS.gguf) | IQ3_XS | 2.51GB | | [NorLlama-3B.IQ3_S.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.IQ3_S.gguf) | IQ3_S | 2.51GB | | [NorLlama-3B.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.Q3_K_S.gguf) | Q3_K_S | 2.51GB | | [NorLlama-3B.IQ3_M.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.IQ3_M.gguf) | IQ3_M | 2.56GB | | [NorLlama-3B.Q3_K.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.Q3_K.gguf) | Q3_K | 2.56GB | | [NorLlama-3B.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.Q3_K_M.gguf) | Q3_K_M | 2.56GB | | [NorLlama-3B.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.Q3_K_L.gguf) | Q3_K_L | 2.59GB | | [NorLlama-3B.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.IQ4_XS.gguf) | IQ4_XS | 2.51GB | | [NorLlama-3B.Q4_0.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.Q4_0.gguf) | Q4_0 | 0.2GB | | [NorLlama-3B.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.IQ4_NL.gguf) | IQ4_NL | 0.49GB | | [NorLlama-3B.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.Q4_K_S.gguf) | Q4_K_S | 2.78GB | | [NorLlama-3B.Q4_K.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.Q4_K.gguf) | Q4_K | 2.82GB | | [NorLlama-3B.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.Q4_K_M.gguf) | Q4_K_M | 2.82GB | | [NorLlama-3B.Q4_1.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.Q4_1.gguf) | Q4_1 | 0.21GB | | [NorLlama-3B.Q5_0.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.Q5_0.gguf) | Q5_0 | 0.22GB | | [NorLlama-3B.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.Q5_K_S.gguf) | Q5_K_S | 2.91GB | | [NorLlama-3B.Q5_K.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.Q5_K.gguf) | Q5_K | 2.94GB | | [NorLlama-3B.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.Q5_K_M.gguf) | Q5_K_M | 2.94GB | | [NorLlama-3B.Q5_1.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.Q5_1.gguf) | Q5_1 | 0.23GB | | [NorLlama-3B.Q6_K.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.Q6_K.gguf) | Q6_K | 3.58GB | | [NorLlama-3B.Q8_0.gguf](https://huggingface.co/RichardErkhov/NorGLM_-_NorLlama-3B-gguf/blob/main/NorLlama-3B.Q8_0.gguf) | Q8_0 | 0.27GB | 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} } ```