Sentence Similarity
sentence-transformers
Safetensors
bert
multilingual
layer-pruning
vocab-pruning
knowledge-distillation
minilm-l12
text-embeddings-inference
Instructions to use gomyk/minilm-student-L6_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-L6_uniform_distilled with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("gomyk/minilm-student-L6_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:
- 7c695e684b763c0191d911b38a88dfbe9f3e4421a67deeecab7b31612e07f052
- Size of remote file:
- 103 MB
- SHA256:
- 2466b501531541f167254eec7b9d38e6bdb50a5f19bfff19537736cfd9d8359a
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