Instructions to use lordtt13/emo-mobilebert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lordtt13/emo-mobilebert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lordtt13/emo-mobilebert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lordtt13/emo-mobilebert") model = AutoModelForSequenceClassification.from_pretrained("lordtt13/emo-mobilebert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87eb021f80ed5c9a938af46f044371525e53d302ab663e9b31a8a953cd93aa74
- Size of remote file:
- 85.1 MB
- SHA256:
- 46a9db2063f45d273056c74d1b685dcb75c669b483c75db788cd92ab539fc566
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