dataset

Can we create a new "Consumer Electronics" category for TechSpecs API https://techspecs.readme.io/.

This is an API that provides the easiest way to get the detailed technical specifications of any consumer electronics product in the world.

• Faker version: 8.1.2
• OS: Windows 10

For locale fr_FR siren() and siret() methods generate incorrect values.
https://faker.readthedocs.io/en/master/locales/fr_FR.html#faker.providers.company.fr_FR.Provider.siren
https://faker.readthedocs.io/en/master/locales/fr_FR.html#faker.providers.company.fr_FR.Provider.siret

A valid SIREN has 9 digits = 8 digits + 1 Luhn Key
A valid SIRET has 14

At the moment, from API there are two useful columns about tasks:

However, in tabs (views) there are possible columns tasks:created_at a

My actions before raising this issue

• Read/searched the docs
• Searched past issues

Option to select chunk sizes does not exist in the CLI

Expected Beh

How to reproduce the behaviour

The error occurs in the Step 5/9 of the docker build process

fetch http://dl-cdn.alpinelinux.org/alpine/v3.11/main/x86_64/APKINDEX.tar.gz
fetch http://dl-cdn.alpinelinux.org/alpine/v3.11/community/x86_64/APKINDEX.tar.gz
WARNING: Ignoring http://dl-cdn.alpinelinux.org/alpine/v3.11/main/x86_64/APKINDEX.tar.gz: BAD signature
WARNING: Ignoring http

🚀 Feature

Motivation

torchtext provide several open source nlp datasets in raw form. These datasets are provide as Iterables. Although there are times when user may prefer map-style datase

欢迎您反馈PaddleNLP使用问题，非常感谢您对PaddleNLP的贡献！
在留下您的问题时，辛苦您同步提供如下信息：

• 版本、环境信息
  1）PaddleNLP和PaddlePaddle版本：请提供您的PaddleNLP和PaddlePaddle版本号，例如PaddleNLP 2.0.4，PaddlePaddle2.1.1
  2）系统环境：请您描述系统类型，例如Linux/Windows/MacOS/，python版本
• 复现信息：如为报错，请给出复现环境、复现步骤
  paddle版本2.0.8 paddlenlp版本2.1.0
  建议，能否在paddlenlp文档中，整理列出各个模型的tokenizer是基于什么类别的based，如bert tokenizer是word piece的，xlnet tokenizer是sentence piece的，以及对应的输入输出样例

Expected Behavior

I want to convert torch.nn.Linear modules to weight drop linear modules in my model (possibly big), and I want to train my model with multi-GPUs. However, I have RuntimeError in my sample code. First, I have _weight_drop() which drops some part of weights in torch.nn.Linear (see the code below).

Actual Behavior

RuntimeError: arguments are located on different GPUs at /

Add a way to change the sample id output in the annotation process to a specific number (see picture).

Reason: I want to annotate large text and the app don't like it when the documents to annotate are too large, so I spitted in a sentence the document but I would like to be able to