Instructions to use argish/text-emotion-classifier-distilroberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use argish/text-emotion-classifier-distilroberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="argish/text-emotion-classifier-distilroberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("argish/text-emotion-classifier-distilroberta") model = AutoModelForSequenceClassification.from_pretrained("argish/text-emotion-classifier-distilroberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d980081bb2906120d141613da50de2298f3d225d91bd65c4068e194771fe44a
- Size of remote file:
- 5.3 kB
- SHA256:
- 2121a10d486100446a277d1d6fa9714c9fe22530e49f9c90facfaadc3f753580
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