Instructions to use Ateeb/EmotionDetector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ateeb/EmotionDetector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ateeb/EmotionDetector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ateeb/EmotionDetector") model = AutoModelForSequenceClassification.from_pretrained("Ateeb/EmotionDetector") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1b2caa8ddcbb7b3c4e9b2b9f13aa816006d1f7b1d99fe02d615508e6c5fe779
- Size of remote file:
- 465 MB
- SHA256:
- 6ff80e092f094bac8d48542ccb09e8c5a32057520f432eedabd4852eba7249ec
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