Instructions to use techthiyanes/chinese_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use techthiyanes/chinese_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="techthiyanes/chinese_sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("techthiyanes/chinese_sentiment") model = AutoModelForSequenceClassification.from_pretrained("techthiyanes/chinese_sentiment") - Notebooks
- Google Colab
- Kaggle
What sentiment does each label represent?
#1
by ZhiL - opened
Hi. Does anyone know what sentiment each label represents? There are five labels, "star 1", "star 2", "star 3", "star 4", "star 5". But it's unclear what each of them means.
5:positive;1:negative
How to change the max length of input
Max length of input is limited to 512 tokens.This model has been trained with limited inputs & limited resources. If length of token needs to be modified then limit the length at tokenizers(Pass max length arguments).
1: Semi-negation
2:Negation
3:Neutral
4:Semi-positive
5:Positive