Text Classification
Transformers
Safetensors
modernbert
multi_label_classification
Generated from Trainer
text-embeddings-inference
Instructions to use angarcme/finetuned_model_emotion_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use angarcme/finetuned_model_emotion_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="angarcme/finetuned_model_emotion_detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("angarcme/finetuned_model_emotion_detection") model = AutoModelForSequenceClassification.from_pretrained("angarcme/finetuned_model_emotion_detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1619c1a210e9b729fe205fa75c9709d13961d2e9ad2b517f99bf402828855324
- Size of remote file:
- 34.4 MB
- SHA256:
- aa6396b645325378a159ce20800b8fdf4d3724306a7d601d47de108272e5761c
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