flair | simple framework for state-of-the-art Natural Language | Natural Language Processing library
kandi X-RAY | flair Summary
kandi X-RAY | flair Summary
A very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends.
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Top functions reviewed by kandi - BETA
- Fetch model from Hugger
- Download a file from cache
- Wrapper for tqdm progress bar
- Return the path to a file or directory
- Evaluate the model
- Get one or more embeddings
- Adds item to index
- Prepare tokens to be embedding
- Adds embeddings to BERT model
- Add embeddings
- Identify column - level annotations
- Extract and convert to Conllu Packet
- Returns a dictionary mapping QID - IDs to wikinames
- Compute embeddings for each sentence
- Predict for given sentences
- Compute the embeddings
- Creates a dictionary of all the wikinames in the list
- Prints the prediction results
- Predict a zero shot
- Generate a label dictionary for each label
- Predict the given sentences
- Predict given sentences
- Decode features_tuple
- Adds embeddings
- Evaluate objective function
- Adds embedding
flair Key Features
flair Examples and Code Snippets
Lines of Code : 74
License : No License
Copydocker run -it -p 5000:5000 samhavens/flair-as-service:en-full
[
{
"text": "George Washington went to the store and chocked on a cherry pit",
"labels": [],
"entities": [
{
"text": "George Washington",
"start_pos": @inproceedings{akbik2018coling,
title={Contextual String Embeddings for Sequence Labeling},
author={Akbik, Alan and Blythe, Duncan and Vollgraf, Roland},
booktitle = {{COLING} 2018, 27th International Conference on Computational Linguistics},
from flair.data import Sentence
from flair.models import SequenceTagger
# make a sentence
sentence = Sentence('I love Berlin .')
# load the NER tagger
tagger = SequenceTagger.load('ner')
# run NER over sentence
tagger.predict(sentence)
# print th import inspect
import json
import logging
import os
import sys
from dataclasses import dataclass, field
import torch
from transformers import HfArgumentParser
import flair
from flair import set_seed
from flair.embeddings import TransformerWordEmbed reddit.subreddit("test").flair.templates
script/
- main.py
- image.png
reddit.subreddit('').submit_image(title, image_path="image.png")
with open ("./txt.txt", mode = "r") as file:
keywords = ['keyword 1', 'keyword 2','keyword 3','keyword 4']
lines = file.readlines()
glitch_flair=False
for lineno, line in enumerate(lines,1):
matches = [k for k in ke!pip3 install flair
import flair
flair_sentiment = flair.models.TextClassifier.load('en-sentiment')
sentence1 = 'the movie received critical acclaim'
sentence2 = 'the movie did not attain critical acclaim'
s1 = fFileNotFoundError: [Errno 2] No such file or directory: 'src/Modules/berkeleydb.h'
!apt search Berkelay
!apt install libdb5.3-dev
!apt install libdb5.3-dev
!pip indf = {
'Submission_Date': ['2021-01-01', '2021-03-01', '2021-03-01', '2021-03-01', '2021-04-01', '2021-04-01'],
'Flair': ['Hedge Fund Tears', 'Hedge Fund Tears', 'Hedge Fund Tears', 'Due Diligence', 'Discussion', 'News']
}
df = pd.driver = webdriver.Chrome(driver_path)
driver.maximize_window()
#driver.implicitly_wait(50)
wait = WebDriverWait(driver, 20)
driver.get("https://www.myntra.com/kurtas/jompers/jompers-men-yellow-printed-straight-kurta/11226756/buy")
ele = WCommunity Discussions
Trending Discussions on flair
QUESTION
Trying to post to a subreddit that requires flairs
...ANSWER
Answered 2022-Mar-21 at 13:29You can find the available flair ids with
QUESTION
I read this line
when you are starting namenode, latest fsimage file is load into “in-memory”. and at the same time, edit log file is also loaded into memory if fsimage file doesn’t contain up-to date information
from https://data-flair.training/forums/topic/in-which-location-namenode-stores-its-metadata-and-why/ they are using term "in-memory" and "memory" are they different ?
...ANSWER
Answered 2022-Mar-07 at 15:17No they aren't different. They are loaded into RandomAccessFile if that helps to think about. For reference here is FSImage. To help you see how this is done.
QUESTION
I am trying to understand the underlying concept in Spark from here. As far as I have understood, narrow transformation produce child RDDs that are transformed from a single parent RDD (might be multiple partitions of the same RDD). However, union and intersection both require two or more RDDs for the transformations to be performed. Can someone please clear this theoretically?
...ANSWER
Answered 2022-Jan-09 at 16:40No, your understanding is incorrect. A a narrow transformation is the one that only requires a single partition from the source to compute all elements of one partition of the output. union is therefore a narrow transformation, because to create an output partition, you only need the single partition from the source data.
Intersection on the other hand is wide, because even for a single partition of the output, it requires access to the entire content of (at least) one of the source rdds.
QUESTION
I have trained my stock price prediction model by splitting the dataset into train & test. I have also tested the predictions by comparing the valid data with the predicted data, and the model works fine. But I want to predict actual future values.
What do I need to change in my code below?
How can I make predictions up to a specific date in the actual future?
Code (in a Jupyter Notebook):
(To run the code, please try it in a similar csv file you have, or install nsepy python library using command pip install nsepy)
ANSWER
Answered 2021-Dec-22 at 10:12Below is an example of how you could implement this approach for your model:
QUESTION
I want to report on the difference between males and female fish in migration tactics. Would this be a chi-squared test? This is my data:
...ANSWER
Answered 2021-Nov-19 at 03:46Now we can create a table and compute Chi square:
QUESTION
So I have my Notebook on Google Colab using Python 3 (and I will implement some Deep learning libraries ex: Keras, TF, Flair, OpenAI...) so I really want to keep using Python 3 and not switch to 2.
However, I have a .db file that I want to open/read, the script is written in Python 2 because they are using bsddb library (which is deprecated and doesn't work on Python 3)
...ANSWER
Answered 2021-Nov-09 at 12:50berkeleydb is only Python binding on database BerkeleyDB created in C/C++.
When I try to install it on my local system Linux Mint then I see error with
QUESTION
i would like to convert a dataframe with calculating percentage points for a graph later on in python.
The current frame looks like this
Post ID Title Url Author Score Submission_Date Total_Num_of_Comments Permalink Flair Selftext TitleAndText Word Count k4nllk Update: Whassup bro? https://www.reddit.com/r/GME/comments/k4nllk/update_whassup_bro/ matt_xndever 1 2021-01-01 16:58:48 13 /r/GME/comments/k4nllk/update_whassup_bro/ Hedge Fund Tears asdasdasd asdasdasdasd 59.0Where flairs are the categories i want to look for (over 40). On one submission day (i want to look onto days only), there can be multiple posts with different flairs. These flairs should add up to 100%.
So i want to create a dataframe like that:
Submission_Date Discussion Due Diligence Hedge Fund Tears News 01.01.2021 NaN NaN 1.0 NaN 03.01.2021 NaN 0.333333 0.666667 NaNMy graph should look like this: Plot stacked (100%) bar chart for multiple categories on multiple dates in Python
Can someone help me with the preparation for that?
Thanks and best regards
...ANSWER
Answered 2021-Oct-03 at 18:11You can approach the problem as follows:
- iterate over unique dates and slice the dataframe for each date
- compute counts for each flair category with pandas
value_counts() - get shares by dividing over the size of each slice
- transpose the pandas series containing the shares for appending
- append the shares for each date
Here is a sample input:
QUESTION
I have an existing ASP.NET Core Angular Web application with the usual flairs. It comes with set of migration scripts (e.g. 20151227555555_AddIdentity.cs, 20161227444444_AddCoreEntities.cs etc) in a Migration/ code folder, each has Up, Down, and BuildTargetModel methods.
then there is another folder called MigrationScript that contains the equivalent of table creation SQL scripts (straight-up CREATE TABLE...) for the various database entities.
I am used to running database management and recreation/restore via a database project that I can "publish". I am new to the EF Migration way of doing it, so how do I run those migration C# scripts to create the database?
ANSWER
Answered 2021-Sep-21 at 19:54The fact that the C# migration scripts already contains Up() and Down() methods means they are ready to be applied. (Note: usually the Up and Down methods are created by the Add-Migration migrationname command).
Here is how to apply the C# entity framework migration scripts in an existing project:
Create the empty database with the correct database name. The database name is usually defined in the
aspsettings.jsonfile underConnectionStringsgroup. Open Microsoft SQL Server Management Studio, create an empty database with the correct name.In Visual Studio Solution Explorer, right-mouse click on the project that contains the
Migrationfolder (where the C# migration scripts are located), chooseManage NuGet Packages...and look underInstalledtab to see ifMicrosoft.EntityFrameWorkCore.Toolspackage is installed, if not go ahead install it. Because that is the package that contains the EF migration commands, i.e.Add-Migration,Update-DatabaseetcWith the
Microsoft.EntityFrameWorkCore.Toolspackage installed in the project that contains theMigrationfolder, open thePackage Manager ConsoleviaTools -> NuGet Package Manager -> Package Manager Consolemenu options.At the
Package Manager Consoleprompt, type the commandUpdate-Database, then all of the migration scripts will be applied and the tables created in the local SQL Server database created in step 1.
QUESTION
Background info: I have some code that should pull results from a subreddit whenever they have the flair "loot", look for codes in the format XXXX-XXXX-XXXX, XXXX-XXXX-XXXX-XXXX, or those two without dashes, and output the codes in the console to be copy-pasted in another window. I also have it output any erroneous codes at the bottom for manual input later. The code runs fine, but the output is not the way that I want it, as explained later.
Currently, the code works perfectly with alphanumeric codes, but gives an error when an "!" is in the code. I have set the range to include !, so I do not know what is setting off the error. I also have the code over at https://www.mycompiler.io/view/EgXpTO0 , which can be run there to see what I see.
...ANSWER
Answered 2021-Aug-25 at 20:46The reason your codes do not work when they end with an "!" is because \b indicates a position of a word boundary ((^\w|\w$|\W\w|\w\W)). ! is not a part of a word.
To fix this, you can use something like: (^(?=[\w!])|(?<=[\w!])$|(?<=[^\w!])(?=[\w!])|(?<=[\w!])(?=[^\w!])) at the end.
This regex is essentially \b, with ! included.
QUESTION
This is my folder structure:
This is how page looks like:
I have got all necessary data from props, but I fail to understand how to generate dynamic id pages. I want to generate dynamic ~/movies/_id pages, based on the id pulled from an array from API. And that pages just have to get Title, picture and overview from API object. So those two are questions.
Movies.vue is parent page. movieComp is component I have used to v-for on, to display list of a movies received from the array from API. Below every movie picture is a details button that should lead to that movie details (based on the id received from API).
_id.vue is a page that I want to display based on the id received from API.
This is code in movies.vue (parent).
...ANSWER
Answered 2021-Aug-13 at 14:30What you need is to create a movies subfolder in which you add _id.vue and movies.vue (renamed index.vue).
You should have the folowing folder structure:
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