Instructions to use Sindhu/emo_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sindhu/emo_roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sindhu/emo_roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sindhu/emo_roberta") model = AutoModelForSequenceClassification.from_pretrained("Sindhu/emo_roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4332d95465f4a00e3910da03e7cd7cc86da2ce7795c4d345edd6c77c3b5cb914
- Size of remote file:
- 499 MB
- SHA256:
- 7d3cd8a450ccdacade558fde5dce0936cb2cb0d1867adeeb33c55fdbdaccd990
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