Instructions to use nanaaaa/BilingualChildEmo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nanaaaa/BilingualChildEmo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nanaaaa/BilingualChildEmo")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nanaaaa/BilingualChildEmo") model = AutoModelForSequenceClassification.from_pretrained("nanaaaa/BilingualChildEmo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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## Environmental Impact
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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