Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use dindanurdz/text_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use dindanurdz/text_classification_model with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("dindanurdz/text_classification_model") - sentence-transformers
How to use dindanurdz/text_classification_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dindanurdz/text_classification_model") 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
- Xet hash:
- 52fe6e5015af15a1f5325c39e48b65f05356a699c819481176db45cf2f0af040
- Size of remote file:
- 69.6 MB
- SHA256:
- 88a4f5070093e5d3771d51f8879c4244c5028b6239ae546d48b5d58fce413d02
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