Instructions to use Cameron/BERT-eec-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cameron/BERT-eec-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cameron/BERT-eec-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cameron/BERT-eec-emotion") model = AutoModelForSequenceClassification.from_pretrained("Cameron/BERT-eec-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c3b343d803517420ee67ba3fa0edd38645cb13e8f661f0ab89e75fe4499d1db
- Size of remote file:
- 433 MB
- SHA256:
- 78ff55fd8fc5ddee83d76e53c383614004066af63e9722e1bd50db25094addef
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