Tensorflow

TensorFlow is an open source library that was created by Google. It is used to design, build, and train deep learning models.
Here are 24,730 public repositories matching this topic...
Related to #5142, AlbertTokenizer
(which uses SentencePiece) doesn't decode special tokens (like [CLS], [MASK]) properly. This issue was discovered when adding the Nystromformer model (#14659), which uses this tokenizer.
To reproduce (Transformers v4.15 or below):
!pip install -q transformers sentencepiece
from transformers import AlbertTokenizer
tokenizer = AlbertTokenizer.from
-
Updated
Feb 5, 2022 - Python
-
Updated
Jan 4, 2022 - Jupyter Notebook
-
Updated
Jan 31, 2022 - Python
-
Updated
Sep 11, 2021 - Python
-
Updated
Feb 3, 2022
-
Updated
Jan 13, 2022 - Jupyter Notebook
-
Updated
Nov 4, 2021 - Python
-
Updated
Jan 2, 2022 - Python
-
Updated
Jan 4, 2022 - C++
-
Updated
Feb 4, 2022 - Go
-
Updated
Jan 25, 2022 - Python
-
Updated
Feb 5, 2022 - JavaScript
-
Updated
Aug 11, 2021 - Jupyter Notebook
-
Updated
Aug 13, 2021 - Jupyter Notebook
-
Updated
Feb 4, 2022 - C++
I've ran into this issue for a couple hours and I ended up editing the dist library adding two new functions called fetchVideo
and bufferToVideo
that works pretty much like the fetchImage
and bufferToImage
functions.
I'll leave it here to help somebody else with the same issue and in case someone wants to include it on future releases.
face-api.js
...
exports.fetchVideo = fetc
Although the results look nice and ideal in all TensorFlow plots and are consistent across all frameworks, there is a small difference (more of a consistency issue). The result training loss/accuracy plots look like they are sampling on a lesser number of points. It looks more straight and smooth and less wiggly as compared to PyTorch or MXNet.
It can be clearly seen in chapter 6([CNN Lenet](ht
-
Updated
Aug 25, 2021 - Python
-
Updated
Aug 30, 2021 - Jupyter Notebook
-
Updated
Feb 4, 2022 - Python
Is your feature request related to a problem? Please describe.
I am uploading our dataset and models for the "Constructing interval measures" method we've developed, which uses item response theory to convert multiple discrete labels into a continuous spectrum for hate speech. Once we have this outcome our NLP models conduct regression rather than classification, so binary metrics are not r
New Operator
Describe the operator
Why is this operator necessary? What does it accomplish?
This is a frequently used operator in tensorflow/keras
Can this operator be constructed using existing onnx operators?
If so, why not add it as a function?
I don't know.
Is this operator used by any model currently? Which one?
Are you willing to contribute it?
Every kubeflow image should be scanned for security vulnerabilities.
It would be great to have a periodic security report.
Each of these images with vulnerability should be patched and updated.
-
Updated
Feb 4, 2022 - Python
-
Updated
Dec 22, 2020 - Python
-
Updated
Jul 25, 2021 - Jupyter Notebook
-
Updated
Jul 1, 2021 - Python
Created by Google Brain Team
Released November 9, 2015
- Organization
- tensorflow
- Website
- www.tensorflow.org
- Wikipedia
- Wikipedia
Current implementation of Go binding can not specify options.
GPUOptions struct is in internal package. And
go generate
doesn't work for protobuf directory. So we can't specify GPUOptions forNewSession
.