Sentence Similarity
sentence-transformers
Safetensors
Kazakh
bert
feature-extraction
kazakh
low-resource
cultural-nlp
multilingual-minilm
Eval Results (legacy)
text-embeddings-inference
Instructions to use crossroderick/minidalalm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use crossroderick/minidalalm with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("crossroderick/minidalalm") 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
| epoch,steps,cosine_accuracy,cosine_accuracy_threshold,cosine_f1,cosine_precision,cosine_recall,cosine_f1_threshold,cosine_ap,cosine_mcc | |
| 0.12711325791280031,1000,0.9999880826113382,0.9995862245559692,0,0,0,0,0.0,0.0 | |
| 0.25422651582560063,2000,0.9999880826113382,0.9996930360794067,0,0,0,0,0.0,0.0 | |
| 0.3813397737384009,3000,0.9999880826113382,0.9997444152832031,0,0,0,0,0.0,0.0 | |