Instructions to use msgfrom96/emotion_model_improved with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use msgfrom96/emotion_model_improved with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="msgfrom96/emotion_model_improved")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("msgfrom96/emotion_model_improved") model = AutoModelForSequenceClassification.from_pretrained("msgfrom96/emotion_model_improved", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| {"thresholds": [0.3678717017173767, 0.19193291664123535, 0.3201530873775482, 0.43696150183677673, 0.34174644947052, 0.3442804515361786, 0.15672166645526886, 0.10731738805770874, 0.28868183493614197, 0.4694070518016815, 0.18090945482254028], "emotions": ["anger", "anticipation", "disgust", "fear", "joy", "sadness", "surprise", "trust", "love", "optimism", "pessimism"]} |