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:
- 2fdf50da66f9ac0d06841bbf0c5907882ad0f322b841ec0e16caf41924d986f8
- Size of remote file:
- 2.24 GB
- SHA256:
- 1ae55f8ecd88415a39d7b74fca17290c63a0759c9b5d05886d602aeb261108c8
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