MIRNet-TFJS
tf-transformers
| MIRNet-TFJS | tf-transformers | |
|---|---|---|
| 7 | 5 | |
| 347 | 84 | |
| - | - | |
| 0.0 | 1.7 | |
| about 1 year ago | about 1 year ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | Apache License 2.0 |
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MIRNet-TFJS
tf-transformers
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Tensorflow-Transformers 2.0 ( for NLP, CV, Audio )
Code : GitHub - legacyai/tf-transformers: State of the art faster Natural Language Processing in Tensorflow 2.0 . 1 Website : https://legacyai.github.io/tf-transformers 1
- [P] Production Ready NLP Deep learning tutorials on tensorflow 2.0. tf-transformers
- Do we really need to Dstill Language Models? Joint loss is all we need - Albert-Joint .
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tf-transformers : State of the art faster NLP in Tensorflow 2.0 . 80 % faster to existing TF based libraries.
Faster Auto Regressive Decoding using Tensorflow2. Faster than PyTorch in most experiments (V100 GPU). 80% faster compared to existing TF based libraries (relative difference) Refer benchmark code.
- [D] Why is tensorflow so hated on and pytorch is the cool kids framework?
What are some alternatives?
super-resolution - Tensorflow 2.x based implementation of EDSR, WDSR and SRGAN for single image super-resolution
medspacy - Library for clinical NLP with spaCy.
labml - 🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱
flax - Flax is a neural network library for JAX that is designed for flexibility.
TFServing-Demos - TF Serving demos
bertviz - BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
FSRCNN-pytorch - PyTorch implementation of Accelerating the Super-Resolution Convolutional Neural Network (ECCV 2016)
BERT-for-Mobile - Compares the DistilBERT and MobileBERT architectures for mobile deployments.
yolov7-tfjs - Object Detection using Yolov7 in tensorflow.js
gpt-3-simple-tutorial - Generate SQL from Natural Language Sentences using OpenAI's GPT-3 Model
TensorFlow2.0_Notebooks - Implementation of a series of Neural Network architectures in TensorFow 2.0
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.