Instructions to use Pendrokar/TorchMoji with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pendrokar/TorchMoji with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Pendrokar/TorchMoji")# Load model directly from transformers import AutoTokenizer, BertForMultilabelSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Pendrokar/TorchMoji") model = BertForMultilabelSequenceClassification.from_pretrained("Pendrokar/TorchMoji", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Original examples for widget
Browse files
README.md
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tags:
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- text-classification
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- emotion
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---
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tags:
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- text-classification
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- emotion
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widget:
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- text: "You love hurting me, huh?"
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- text: "I know good movies, this ain't one"
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- text: "It was fun, but I'm not going to miss you"
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- text: "My flight is delayed.. amazing."
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- text: "What is happening to me??"
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- text: "This is the shit!"
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