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Malkovsky/load-balancing 1

Testint load balancing algorithms

Malkovsky/Accelerated-consensus 0

Simulation of network consensus with some acceleration techniques

Malkovsky/AU_slides 0

Material for academic university "Optimization methods" course

Malkovsky/co-mkn-hw-2021 0

Convex optimization course 2021 homework repository

Malkovsky/darts 0

Differentiable architecture search for convolutional and recurrent networks

Malkovsky/distributed-learning 0

Repository for experimenting with consensus based distributed learning algorithms

Malkovsky/football_bot 0

A support bot for planning vacation football events

create barnchMalkovsky/NeMo

branch : feature/microphone_beam_search_demo

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commit sha ce36686fdf63b01784cc955fa5b2f9fc4b2dc955

feat: updated with prefix detach

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commit sha c2e8f170efb0520feb6d97bb1455d7553b0e3378

fix: doc comments

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feat: added notebook with levenstein heuristics, beam search and hypothesis tree

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create barnchMalkovsky/co-mkn-hw-2021

branch : master

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issue commentNVIDIA/NeMo

Online Microphone ASR (ERROR: No audio input device found.)

getAudio() method described here https://github.com/ricardodeazambuja/colab_utils/blob/master/colab_utils/init.py actually uses microphone from the user browser in colab

Rajratnpranesh

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commit sha 5b905358a519a692cce561b2240da297849c3550

fix: internal imports

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issue openedkpu/kenlm

Are there different states or every model uses general purpose lm::model::State?

According to https://github.com/kpu/kenlm/blob/master/lm/virtual_interface.hh#L71 https://github.com/kpu/kenlm/blob/master/lm/facade.hh#L14 Every model should have its own type of state, but from https://github.com/kpu/kenlm/blob/master/lm/model.hh#L30 https://github.com/kpu/kenlm/blob/master/lm/model.hh#L136 it looks like every one of them uses general state type https://github.com/kpu/kenlm/blob/master/lm/state.hh#L15 which makes trie-based models not that effective.

I'm wondering whether there are different type of states or no?

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added ford-fulkerson example

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