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") - Notebooks
- Google Colab
- Kaggle
Create README.md
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by Heng666 - opened
README.md
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---
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license: openrail
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datasets:
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- imdb
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language:
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- en
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co2_eq_emissions:
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Hardware Type: 1 x NVIDIA A100-SXM4-40GB
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Seconds used: 25.82108235359192
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Cloud Provider: Colab
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Compute Region: Singapore(SGP)
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emissions: 0.0012207030395688
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---
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