Sentence Similarity
sentence-transformers
Safetensors
bert
multilingual
layer-pruning
vocab-pruning
knowledge-distillation
minilm-l12
text-embeddings-inference
Instructions to use gomyk/minilm-student-L4_uniform_distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use gomyk/minilm-student-L4_uniform_distilled with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("gomyk/minilm-student-L4_uniform_distilled") 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:
- 23cfeb1faeee8da96e5e92683ea1601ac577201b689e2c53889d8c055d6d1ec8
- Size of remote file:
- 88.7 MB
- SHA256:
- 849314db7a40fefcafc751585b9a2004108365166b922a06d5c979451da025e4
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