Simple Content Platform
to manage any structured content
A self-hosted headless and api-driven CMS
Build. Connect. Deliver.
$ curl 'https://domain.com/api/collections/get/posts?token=e37c44cd4c67fbf3'
[
{
"_id": "34hgj4892381b31134mkl",
"title": "Hello World",
"content": "...",
"tags": ["info"]
},
{
"_id": "34hgj4892381b31134mkl",
"title": "First Post",
"content": "...",
"tags": ["general"]
}
]
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Why Cockpit?
Self-hosted
Keep complete control. Your data is and will be always yours.
Open Source
We Open Source and Cockpit is our contribution we would like to share with the world.
Clients will love it
Cockpit comes with an intuitive design and UX which makes it a joy to manage the content.
Cockpit is awesome if you need a flexible content structure but don't want to be limited in how to use the content. Cockpit is a perfect match if you want to support multiple devices or need a content management UI for static site builders. Build unique applications and let Cockpit feed them with content.
Cross-Channel Content Distribution
Web, App, Smart Device, IoT
Some key features
-
Dead simple installation in less than one minute. Kickstart your your next project without any hassle.
-
A simple but powerful headless CMS that is built around an API-first and JSON content approach.
-
SQLite or MongoDB, your choice. Use Cockpit for quick and simple projects or utilize MongoDB for larger ones.
-
A system which invites to extend with custom code. Build a solution to any problem.
-
Cockpit is not a web site builder. It is a content provider. Consume the content the way you want.
@getcockpit + @nuxt_js = best self-hosted, headless CMS solution I've seen to date. Working on a prototype now. So far it's working better than I expected! #VueJS
— Chris Schweda (@metaincognita) 27. April 2018
I may have reached fully static + CMS sourced nirvana with @nuxt_js and @getcockpit.
— Stephen Hallgren (@Teevio) 12. Februar 2018
Stunning headless API first CMS > https://t.co/1K2gUWrBVZ Perfect tag team with #VueJS @getcockpit #JAM #SSG #gohugo
— Gommaar Delneste (@gdelneste) 22. November 2017
Tried @getcockpit #apidrivenCMS for the first time and it’s amazing #JAMstack
— Timo Burmeister (@timo_burmeister) 22. November 2017
@getcockpit your CMS is awesome, thanks a lot
— Michaël Villeneuve (@michael_vil) 29. Februar 2016
After testing, i think that @getcockpit is going to be the CMS of my next project. A perfect approach and i can keep Laravel #dev #cms
— jc suzanne (@jcsuzanne) 26. Oktober 2014
Handling forms with @getcockpit is such a breeze, I love it.
— CoderMcCodeFace (@dupertuiseric) 28. Oktober 2015
so glad i finally found @getcockpit - a simple, user friendly CMS that is -wait for it- unopinionated about your front end #finally
— Angelina Bethoney (@oxangiemarie) 17. Juli 2015
I think I may have just found my new cms @getcockpit . API driven and it's open source! Just what I've been looking for. Awesome!
— DeAndre (@drePHRESHR) 29. Juli 2014
Check out @getcockpit, it is amazing, Where have you been all my life! #PHP
— David D'hont (@Blaxus) 22. August 2015
Looking for a kickass tool to create b-office quickly with a REST API, users... check http://t.co/WqTT1XaxGJ. Thx @getcockpit. :) #awesome
— Olivier Destenay (@_tsbits) 21. April 2015
Just installed @getcockpit; If you're a web developer, this is a must-check-out #cokcpit #cms #php
— Jesse Luoto (@luotojesse) 4. Juli 2014


--- title: Custom Glue keywords: fastai sidebar: home_sidebar summary: "glue between fastai and hugging face's transformers" ---
/home/andreas/anaconda3/envs/nbdev/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_qint8 = np.dtype([("qint8", np.int8, 1)]) /home/andreas/anaconda3/envs/nbdev/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_quint8 = np.dtype([("quint8", np.uint8, 1)]) /home/andreas/anaconda3/envs/nbdev/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_qint16 = np.dtype([("qint16", np.int16, 1)]) /home/andreas/anaconda3/envs/nbdev/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_quint16 = np.dtype([("quint16", np.uint16, 1)]) /home/andreas/anaconda3/envs/nbdev/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_qint32 = np.dtype([("qint32", np.int32, 1)]) /home/andreas/anaconda3/envs/nbdev/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. np_resource = np.dtype([("resource", np.ubyte, 1)]) /home/andreas/anaconda3/envs/nbdev/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_qint8 = np.dtype([("qint8", np.int8, 1)]) /home/andreas/anaconda3/envs/nbdev/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_quint8 = np.dtype([("quint8", np.uint8, 1)]) /home/andreas/anaconda3/envs/nbdev/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_qint16 = np.dtype([("qint16", np.int16, 1)]) /home/andreas/anaconda3/envs/nbdev/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_quint16 = np.dtype([("quint16", np.uint16, 1)]) /home/andreas/anaconda3/envs/nbdev/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_qint32 = np.dtype([("qint32", np.int32, 1)]) /home/andreas/anaconda3/envs/nbdev/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. np_resource = np.dtype([("resource", np.ubyte, 1)])
class
CustomTransformerModel
[source]
CustomTransformerModel
(transformer_model
:PreTrainedModel
) ::Module
Base class for all neural network modules.
Your models should also subclass this class.
Modules can also contain other Modules, allowing to nest them in a tree structure. You can assign the submodules as regular attributes::
import torch.nn as nn
import torch.nn.functional as F
class Model(nn.Module):
def __init__(self):
super(Model, self).__init__()
self.conv1 = nn.Conv2d(1, 20, 5)
self.conv2 = nn.Conv2d(20, 20, 5)
def forward(self, x):
x = F.relu(self.conv1(x))
return F.relu(self.conv2(x))
Submodules assigned in this way will be registered, and will have their
parameters converted too when you call :meth:to
, etc.
class
TransformersBaseTokenizer
[source]
TransformersBaseTokenizer
(pretrained_tokenizer
:PreTrainedTokenizer
,model_type
='bert'
, **kwargs
) ::BaseTokenizer
Wrapper around PreTrainedTokenizer to be compatible with fast.ai
class
TransformersVocab
[source]
TransformersVocab
(tokenizer
:PreTrainedTokenizer
) ::Vocab
Contain the correspondence between numbers and tokens and numericalize.


Vibe Check
The best playlist generator on this corner of internet!
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Groups multiple buttons and other widgets into one visual set.
Want to learn more about the controlgroup widget? Check out the API documentation.


P4Convert: User Guide
April 2015
Copyright © 2007-2015 Perforce Software.
All rights reserved.
P4Convert is supplied by Perforce Software in the hope that it will be useful. It is a support utility, not a Perforce product. All use of this software is at the user's own risk and subject to the following terms and conditions.
THIS SOFTWARE IS PROVIDED BY PERFORCE SOFTWARE, INC. 'AS IS' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL PERFORCE SOFTWARE, INC.