Instructions to use Sp1786/mutliclass-sentiment-analysis-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sp1786/mutliclass-sentiment-analysis-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sp1786/mutliclass-sentiment-analysis-bert")# Load model directly from transformers import AutoTokenizer, SentimentClassifier tokenizer = AutoTokenizer.from_pretrained("Sp1786/mutliclass-sentiment-analysis-bert") model = SentimentClassifier.from_pretrained("Sp1786/mutliclass-sentiment-analysis-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: apache-2.0
datasets:
- Sp1786/multiclass-sentiment-analysis-dataset
language:
- en
metrics:
- bleu
- sacrebleu
library_name: transformers
pipeline_tag: text-classification
tags:
- code