Instructions to use seanpe200/TruthNN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seanpe200/TruthNN with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="seanpe200/TruthNN")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("seanpe200/TruthNN", dtype="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: mit
datasets:
- upasanachatterjee/AllSides-random-split
- mediabiasgroup/BABE
language:
- en
metrics:
- mae
base_model:
- google-bert/bert-base-uncased
library_name: transformers
tags:
- text-classification
- political-bias
- news
- pytorch
- bert