Instructions to use ThinkCERCA/counterargument_hugging with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThinkCERCA/counterargument_hugging with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ThinkCERCA/counterargument_hugging")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ThinkCERCA/counterargument_hugging") model = AutoModelForSequenceClassification.from_pretrained("ThinkCERCA/counterargument_hugging") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("ThinkCERCA/counterargument_hugging")
model = AutoModelForSequenceClassification.from_pretrained("ThinkCERCA/counterargument_hugging")Quick Links
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ThinkCERCA/counterargument_hugging")