# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("ARISCOT/Digital_Literacy_Fact_Checker", dtype="auto")Digital Literacy Fact Checker
This model is designed to classify misinformation across social media, politics, health, science, religion, and agriculture.
NOTICE
Digital Literacy & Fact-Checker AI (Ghana Edition) Copyright 2026 George Asomaning Peprah
This project is licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
ATTRIBUTION
This model was developed by George Asomaning Peprah as part of a mission to improve digital literacy and combat misinformation in Ghana and West Africa.
The model incorporates weights and/or data inspired by or derived from:
- LIAR Dataset
- FEVER Dataset
- Misinformation-Guard
- Custom Ghanaian Digital Literacy benchmarks
Any redistribution of this model or derivative works MUST include this NOTICE file in its entirety.
Model tree for ARISCOT/Digital_Literacy_Fact_Checker
Base model
FacebookAI/roberta-base
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ARISCOT/Digital_Literacy_Fact_Checker")