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
| { | |
| "word_embedding_dimension": 384, | |
| "pooling_mode_cls_token": false, | |
| "pooling_mode_mean_tokens": true, | |
| "pooling_mode_max_tokens": false, | |
| "pooling_mode_mean_sqrt_len_tokens": false, | |
| "pooling_mode_weightedmean_tokens": false, | |
| "pooling_mode_lasttoken": false, | |
| "include_prompt": true | |
| } |