2024 / Week 26

ONNX Concepts - ONNX 1.17.0 documentation

ONNX can be compared to a programming language specialized in mathematical functions. It defines all the necessary operations a machine learning model needs to implement its inference function with this language. A linear regression could be represented in the following way:

ONNX Concepts - ONNX 1.17.0 documentation

https://onnx.ai/onnx/intro/concepts.html

Nx vs. Python performance for sentence-transformer encoding

Hey, I found this thread very helpful, but I would like to ask some additional questions / clarifications! I am trying to speed up some text_embedding creations. I have a data migration where we want to back-fill embeddings for existing entries. I tried various batch sizes for this and settled on 500. I tried to create the changesets with the embedding with Enum.map and Task.async_stream. But they yield the same time. I realized that all the time is spend on generating the embedding. I also...

Nx vs. Python performance for sentence-transformer encoding

https://elixirforum.com/t/nx-vs-python-performance-for-sentence-transformer-encoding/56502?page=2

Nx vs. Python performance for sentence-transformer encoding

good discussion on nx vs python performance, also nx vs ortex way

GitHub - snakers4/silero-models: Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple

Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple - snakers4/silero-models

GitHub - snakers4/silero-models: Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple

https://github.com/snakers4/silero-models?tab=readme-ov-file#denoise

GitHub - snakers4/silero-models: Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple

denoise model