Finetuned models
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How to use KBLab/robust-swedish-sentiment-multiclass with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="KBLab/robust-swedish-sentiment-multiclass") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("KBLab/robust-swedish-sentiment-multiclass")
model = AutoModelForSequenceClassification.from_pretrained("KBLab/robust-swedish-sentiment-multiclass")The National Library of Sweden/KBLab releases a robust, multi-label sentiment classifier finetuned on Megatron-BERT-large-165K. The model was trained on approximately 75K Swedish texts from multiple linguistic domains and datasets.
There is a post on the KBLab blog describing the model in further detail.
@misc{hägglöf2023a,
author = {Hägglöf, Hillevi},
title = {The KBLab Blog: A robust, multi-label sentiment classifier for Swedish},
url = {https://kb-labb.github.io/posts/2023-06-16-a-robust-multi-label-sentiment-classifier-for-swedish/},
year = {2023}
}