Base Models
Collection
This collection includes all NorGLM base models pretrained from scratch • 4 items • Updated
How to use NorGLM/NorGPT-3B with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="NorGLM/NorGPT-3B") # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("NorGLM/NorGPT-3B")
model = AutoModelForCausalLM.from_pretrained("NorGLM/NorGPT-3B")How to use NorGLM/NorGPT-3B with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "NorGLM/NorGPT-3B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "NorGLM/NorGPT-3B",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'docker model run hf.co/NorGLM/NorGPT-3B
How to use NorGLM/NorGPT-3B with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "NorGLM/NorGPT-3B" \
--host 0.0.0.0 \
--port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "NorGLM/NorGPT-3B",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'docker run --gpus all \
--shm-size 32g \
-p 30000:30000 \
-v ~/.cache/huggingface:/root/.cache/huggingface \
--env "HF_TOKEN=<secret>" \
--ipc=host \
lmsysorg/sglang:latest \
python3 -m sglang.launch_server \
--model-path "NorGLM/NorGPT-3B" \
--host 0.0.0.0 \
--port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "NorGLM/NorGPT-3B",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'How to use NorGLM/NorGPT-3B with Docker Model Runner:
docker model run hf.co/NorGLM/NorGPT-3B
Gnerative Pretrained Tranformer with 3 Billion parameters for Norwegian.
It belongs to NorGLM, a suite of pretrained Norwegian Generative Language Models (NorGLMs). The model is based on GPT2 architecture. NorGLM can be used for non-commercial purposes.
All models in NorGLM are trained on 200G datasets, nearly 25B tokens, including Norwegian, Denish, Swedish, Germany and English.
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
model_id = "NorGLM/NorGPT-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)
If you feel our work is helpful, please cite our papers:
@article{gulla2026norwai,
title={NorwAI's Large Language Models: Technical Report},
author={Gulla, Jon Atle and Liu, Peng and Zhang, Lemei},
journal={arXiv preprint arXiv:2601.03034},
year={2026}
}
@inproceedings{liu2024nlebench+,
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 and Lauvrak, Even and Ingvaldsen, Jon and Eide, Simen and Gulla, Jon Atle and Yang, Zhirong},
booktitle={Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing},
pages={5543--5560},
year={2024}
}