Instructions to use rahulkhandelw/MoodPrediction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rahulkhandelw/MoodPrediction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="rahulkhandelw/MoodPrediction")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("rahulkhandelw/MoodPrediction") model = AutoModelForTokenClassification.from_pretrained("rahulkhandelw/MoodPrediction") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 111b38a610e5aa481054484c2c97d192a1934c0c9db118a7748128508858068d
- Size of remote file:
- 265 MB
- SHA256:
- de28daf6c052b4587dd9c83f569849d88eb4908e368d85a1a43c24dc0dddf747
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