Implementing Automatic Filtering with PyTorch and Transformersby@feedbackloop

Implementing Automatic Filtering with PyTorch and Transformers

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Dive into the world of automatic content filtering implemented with PyTorch and Transformers. Utilizing the allmpnet-base-v2 Sentence-Transformer, powered by a Tesla V100-SXM3 GPU, this 12-layer Transformer model calculates cosine similarity, achieving efficiency in content evaluation with an average runtime of 76 minutes per dataset.
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by The FeedbackLoop: #1 in PM Education @feedbackloop.The FeedbackLoop offers premium product management education, research papers, and certifications. Start building today!
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