courage622's Stars
xorbitsai/inference
Replace OpenAI GPT with another LLM in your app by changing a single line of code. Xinference gives you the freedom to use any LLM you need. With Xinference, you're empowered to run inference with any open-source language models, speech recognition models, and multimodal models, whether in the cloud, on-premises, or even on your laptop.
davabase/whisper_real_time
Real time transcription with OpenAI Whisper.
facebook/Ax
Adaptive Experimentation Platform
espnet/espnet
End-to-End Speech Processing Toolkit
yangyangwithgnu/use_vim_as_ide
use vim as IDE
jhclark/bigfatlm
Hadoop MapReduce training of modified Kneser-Ney smoothed language models
nndl/nndl.github.io
《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning
wbengine/SPMILM
ucam-smt/sgnmt
Decoding platform for machine translation research
lmthang/thesis
Thang Luong's thesis on Neural Machine Translation
clab/fast_align
Simple, fast unsupervised word aligner
moses-smt/giza-pp
GIZA++ is a statistical machine translation toolkit that is used to train IBM Models 1-5 and an HMM word alignment model. This package also contains the source for the mkcls tool which generates the word classes necessary for training some of the alignment models.
vahidk/EffectiveTensorflow
TensorFlow tutorials and best practices.
HIT-SCIR/ltp
Language Technology Platform
yandex/faster-rnnlm
Faster Recurrent Neural Network Language Modeling Toolkit with Noise Contrastive Estimation and Hierarchical Softmax
kaldi-asr/kaldi
kaldi-asr/kaldi is the official location of the Kaldi project.
EdinburghNLP/nematus
Open-Source Neural Machine Translation in Tensorflow
Avmb/deep-nmt-architectures
Training scripts for paper Miceli Barone et al. 2017 "Deep Architectures for Neural Machine Translation"
heri/tensorflow-RNN
Using Google's tensorflow for language modeling with recurrent neural networks
tensorflow/tensorflow
An Open Source Machine Learning Framework for Everyone
tensorflow/tensor2tensor
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.