Instructions to use ARISCOT/Digital_Literacy_Fact_Checker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ARISCOT/Digital_Literacy_Fact_Checker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ARISCOT/Digital_Literacy_Fact_Checker")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ARISCOT/Digital_Literacy_Fact_Checker", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| 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. | |
| --- | |
| 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. |