Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use quantisan/paraphrase-MiniLM-L3-v2-93dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use quantisan/paraphrase-MiniLM-L3-v2-93dataset with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("quantisan/paraphrase-MiniLM-L3-v2-93dataset") - sentence-transformers
How to use quantisan/paraphrase-MiniLM-L3-v2-93dataset with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("quantisan/paraphrase-MiniLM-L3-v2-93dataset") 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
| { | |
| "__version__": { | |
| "sentence_transformers": "3.2.0", | |
| "transformers": "4.45.2", | |
| "pytorch": "2.4.1+cu124" | |
| }, | |
| "prompts": {}, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": null | |
| } |