Speed up your Cosine Similarity for SBERT sentence embeddings via Sentence Transformers (SBERT 17)
Code shows speed improvements in COLAB for cosine similarity for SBERT:
(a) new & improved pre-trained SentenceTransformer models (HuggingFace) and
(b) utilizing normalized tensors with dot product instead of cosine similarity operators for SBERT sentence embeddings.
Beware of model specific fluctuations. Results may vary based on different use cases and will depend on variable GPU loads at different times.
#sbert
#datascience
#dataanalytics
#nlptechniques
#clustering
#semantic
#bert
#3danimation
#3dvisualization
#topologicalspace
#deeplearning
#machinelearningwithpython
#pytorch
#sentence
#embedding
#complex
#umap
#insight
#algebraic_topology
#code_your_own_AI
#SentenceTransformers
#code
#code_in_real_time
Видео Speed up your Cosine Similarity for SBERT sentence embeddings via Sentence Transformers (SBERT 17) канала code_your_own_AI
(a) new & improved pre-trained SentenceTransformer models (HuggingFace) and
(b) utilizing normalized tensors with dot product instead of cosine similarity operators for SBERT sentence embeddings.
Beware of model specific fluctuations. Results may vary based on different use cases and will depend on variable GPU loads at different times.
#sbert
#datascience
#dataanalytics
#nlptechniques
#clustering
#semantic
#bert
#3danimation
#3dvisualization
#topologicalspace
#deeplearning
#machinelearningwithpython
#pytorch
#sentence
#embedding
#complex
#umap
#insight
#algebraic_topology
#code_your_own_AI
#SentenceTransformers
#code
#code_in_real_time
Видео Speed up your Cosine Similarity for SBERT sentence embeddings via Sentence Transformers (SBERT 17) канала code_your_own_AI
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