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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ab4f5922b65bdf686d50568a2c32277b9f39789e5b05e5245d8c97bea853e13
- Size of remote file:
- 465 MB
- SHA256:
- 3a2a16a5311ac46ac6626712a4da7fef4a594e2d2f7109cf5f188bf2336a7b92
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