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: | |
| emissions: 1.2207030395688 | |
| source: "from AutoTrain, code carbon" | |
| training_type: "fine-tuning" | |
| geographical_location: "Singapore(SGP)" | |
| hardware_used: "1 x NVIDIA A100-SXM4-40GB" | |