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
File size: 441 Bytes
344b3c8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"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"
]
} |