Text Classification
sentence-transformers
Safetensors
English
hybrid-sentiment-classifier
sentiment-analysis
multiclass-classification
xgboost
reddit
hybrid-model
Instructions to use mahekgheewala/sentimental_analysis_updated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mahekgheewala/sentimental_analysis_updated with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mahekgheewala/sentimental_analysis_updated") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_type": "hybrid-sentiment-classifier", | |
| "architecture": "sentence-transformers + xgboost", | |
| "base_model": "paraphrase-mpnet-base-v2", | |
| "num_classes": 3, | |
| "class_names": [ | |
| "Negative", | |
| "Positive", | |
| "Neutral" | |
| ], | |
| "test_accuracy": 0.9966352624495289 | |
| } |