Instructions to use msgfrom96/emotion_model_improved with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use msgfrom96/emotion_model_improved with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="msgfrom96/emotion_model_improved")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("msgfrom96/emotion_model_improved") model = AutoModelForSequenceClassification.from_pretrained("msgfrom96/emotion_model_improved") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0f3614175b3a14f57ed3509df12fb4bd99fa6e6cf49afc7aca61445626ebbc74
- Size of remote file:
- 5.3 kB
- SHA256:
- bf4b68cb6d4e4cbac213b3c4b62d9a55bcbf5cfaee34ec62df5739f7bc940664
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