Sentence Similarity
sentence-transformers
Safetensors
Norwegian
Norwegian Nynorsk
Norwegian Bokmål
feature-extraction
dense
custom_code
Eval Results (legacy)
Instructions to use Fremtind/norsbert4-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Fremtind/norsbert4-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Fremtind/norsbert4-large", trust_remote_code=True) sentences = [ "En gruppe barn leker og har det gøy.", "Barn leker på gresset omgitt av sterke farger.", "Barna er sammen.", "Barna leser bøker." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| from __future__ import annotations | |
| import json | |
| from pathlib import Path | |
| import copy | |
| from transformers.configuration_utils import PretrainedConfig | |
| class GptBertConfig(PretrainedConfig): | |
| def __init__( | |
| self, | |
| config_file: Path | str | None = None, | |
| **kwargs | |
| ): | |
| super().__init__(**kwargs) | |
| self.model = "norbert4" | |
| if config_file is not None: | |
| if type(config_file) is str: | |
| config_file = Path(config_file) | |
| assert type(config_file) is not Path, "The config_file should either be a Path or str" | |
| with config_file.open("r") as file: | |
| config = json.load(file) | |
| for attr, value in config.items(): | |
| if isinstance(value, str): | |
| value = value.lower() | |
| setattr(self, attr, value) | |
| for attr, value in kwargs.items(): | |
| if isinstance(value, str): | |
| value = value.lower() | |
| setattr(self, attr, value) | |