Instructions to use avichr/hebEMO_surprise with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use avichr/hebEMO_surprise with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="avichr/hebEMO_surprise")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("avichr/hebEMO_surprise") model = AutoModelForSequenceClassification.from_pretrained("avichr/hebEMO_surprise", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ec24b12b3e0231de9fd2b17aedae2f2989017885d233346e9d4d60512e09a16
- Size of remote file:
- 438 MB
- SHA256:
- 1466d874de586134036cf4f62aa329bf4047cb3d82a7a5a815b9afc99b249310
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