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
File size: 275 Bytes
99561ed | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"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
} |