Instructions to use shichenghu/hw1-hc3-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shichenghu/hw1-hc3-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shichenghu/hw1-hc3-detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("shichenghu/hw1-hc3-detector") model = AutoModelForSequenceClassification.from_pretrained("shichenghu/hw1-hc3-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
CS 546 HW1 HC3 Detector
Name: Shicheng Hu
NetID: shu40
Binary classifier for distinguishing human-written and ChatGPT-generated answers on the HC3 dataset.
Model
Base model: sentence-transformers/all-MiniLM-L6-v2
Fine-tuned for binary sequence classification:
0: Human1: ChatGPT
Results
- Baseline accuracy: 0.8449
- Fine-tuned test accuracy: 0.9846
Course
CS 546 — Advanced Topics in Natural Language Processing
Homework 1
- Downloads last month
- 29