Feature Extraction
sentence-transformers
Safetensors
xlm-roberta
sentence-similarity
Generated from Trainer
dataset_size:1879136
loss:CachedGISTEmbedLoss
text-embeddings-inference
Instructions to use smartmind/KURE-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use smartmind/KURE-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("smartmind/KURE-v1") 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": "4.1.0", | |
| "transformers": "4.51.3", | |
| "pytorch": "2.7.0" | |
| }, | |
| "prompts": {}, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": "cosine" | |
| } |