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", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ateeb/EmotionDetector") model = AutoModelForSequenceClassification.from_pretrained("Ateeb/EmotionDetector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0cf0a4502ee6a80b3dbdcef5e098fccfc7fe8d63f4196756c2463fbf856affbc
- Size of remote file:
- 465 MB
- SHA256:
- 5f6097c47c3bbbc62f82a6b92f9aa32dcc74107c970dad1da19cac79c0b6c23f
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