Instructions to use Heng666/codecarbon-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Heng666/codecarbon-text-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Heng666/codecarbon-text-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Heng666/codecarbon-text-classification") model = AutoModelForSequenceClassification.from_pretrained("Heng666/codecarbon-text-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: openrail | |
| datasets: | |
| - imdb | |
| language: | |
| - en | |
| co2_eq_emissions: | |
| Hardware Type: 1 x NVIDIA A100-SXM4-40GB | |
| Seconds used: 25.82108235359192 | |
| Cloud Provider: Colab | |
| Compute Region: Singapore(SGP) | |
| emissions: 0.0012207030395688 | |