RichardErkhov/NorGLM_-_NorLlama-3B-gguf

Quantization made by Richard Erkhov.

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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	Q2_K	2.51GB
NorLlama-3B.IQ3_XS.gguf	IQ3_XS	2.51GB
NorLlama-3B.IQ3_S.gguf	IQ3_S	2.51GB
NorLlama-3B.Q3_K_S.gguf	Q3_K_S	2.51GB
NorLlama-3B.IQ3_M.gguf	IQ3_M	2.56GB
NorLlama-3B.Q3_K.gguf	Q3_K	2.56GB
NorLlama-3B.Q3_K_M.gguf	Q3_K_M	2.56GB
NorLlama-3B.Q3_K_L.gguf	Q3_K_L	2.59GB
NorLlama-3B.IQ4_XS.gguf	IQ4_XS	2.51GB
NorLlama-3B.Q4_0.gguf	Q4_0	0.2GB
NorLlama-3B.IQ4_NL.gguf	IQ4_NL	0.49GB
NorLlama-3B.Q4_K_S.gguf	Q4_K_S	2.78GB
NorLlama-3B.Q4_K.gguf	Q4_K	2.82GB
NorLlama-3B.Q4_K_M.gguf	Q4_K_M	2.82GB
NorLlama-3B.Q4_1.gguf	Q4_1	0.21GB
NorLlama-3B.Q5_0.gguf	Q5_0	0.22GB
NorLlama-3B.Q5_K_S.gguf	Q5_K_S	2.91GB
NorLlama-3B.Q5_K.gguf	Q5_K	2.94GB
NorLlama-3B.Q5_K_M.gguf	Q5_K_M	2.94GB
NorLlama-3B.Q5_1.gguf	Q5_1	0.23GB
NorLlama-3B.Q6_K.gguf	Q6_K	3.58GB
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

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

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}
}