Instructions to use nateraw/codecarbon-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nateraw/codecarbon-text-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nateraw/codecarbon-text-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nateraw/codecarbon-text-classification") model = AutoModelForSequenceClassification.from_pretrained("nateraw/codecarbon-text-classification") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#5 opened over 2 years ago
by
librarian-bot
Adding `safetensors` variant of this model
#4 opened over 2 years ago
by
SFconvertbot
Align label mapping with imdb dataset
1
#3 opened almost 4 years ago
by
lewtun