Instructions to use Ateeb/FullEmotionDetector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ateeb/FullEmotionDetector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ateeb/FullEmotionDetector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ateeb/FullEmotionDetector") model = AutoModelForSequenceClassification.from_pretrained("Ateeb/FullEmotionDetector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d74d3281f4339dbef3196e930a3ef7384622acf6e233a82da95e485c9e89fa9f
- Size of remote file:
- 465 MB
- SHA256:
- ec4670e51928f06d7abf3f9e14f2dbd3cd0d6f9ef023714250dbac9c6a8b26c7
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