Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use PrashantG6838/theme_tagging with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use PrashantG6838/theme_tagging with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("PrashantG6838/theme_tagging") - sentence-transformers
How to use PrashantG6838/theme_tagging with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("PrashantG6838/theme_tagging") 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
| { | |
| "normalize_embeddings": false, | |
| "labels": [ | |
| "Distance and Accessibility Issues", | |
| "Early Marriage", | |
| "Legal Document linked Barriers", | |
| "Other Factors", | |
| "Parental Attitudes and Socio-Cultural Barriers", | |
| "Poverty and Economic Barriers", | |
| "Safety Concerns", | |
| "School Infrastructure and Facility Issues", | |
| "Substance Abuse and Addiction", | |
| "Teacher Capacity and Quality Issues", | |
| "Unknown/Unclear" | |
| ] | |
| } |