Text Classification
sentence-transformers
Joblib
Safetensors
English
bert
sentence-embeddings
mental-health
binary-classification
logistic-regression
text-embeddings-inference
Instructions to use AbdullahImran/Fine-Tuned-SBERT-MiniLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AbdullahImran/Fine-Tuned-SBERT-MiniLM with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AbdullahImran/Fine-Tuned-SBERT-MiniLM") 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
Commit History
-
Upload README.md with huggingface_hub
Verified signature4818c45 -
Delete files pytorch_model.bin with huggingface_hub
Verified signature19897fb -
Upload 1_Pooling/config.json with huggingface_hub
Verified signature1c34aec -
Upload tokenizer_config.json with huggingface_hub
Verified signaturec905e25 -
Upload special_tokens_map.json with huggingface_hub
Verified signature2c0bad4 -
Upload config_sentence_transformers.json with huggingface_hub
Verified signature82547bf -
Upload config.json with huggingface_hub
Verified signature5bdca18 -
Upload model.safetensors with huggingface_hub
Verified signaturee13e1a4 -
Upload logistic_regression_classifier.joblib with huggingface_hub
Verified signature20698e9 -
Upload folder using huggingface_hub
Verified signature435cdff -
initial commit
Verified signatureba8c70f