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Allan Jie allanj

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@allanj
allanj / Random Images on Refresh
Created Jun 15, 2020 — forked from stephenscaff/Random Images on Refresh
Super simple way to randomly load new images on refresh via Jquery and DOM injection. Great for banners.
View Random Images on Refresh
<!DOCTYPE html>
<head>
<!--Little CSS fade in -->
<style>
.fade-in{
-webkit-animation: fade-in 2s ease;
-moz-animation: fade-in ease-in-out 2s both;
-ms-animation: fade-in ease-in-out 2s both;
-o-animation: fade-in ease-in-out 2s both;
@allanj
allanj / Install
Created Jun 5, 2020 — forked from ines/Install
Streamlit + spaCy
View Install
pip install streamlit
pip install spacy
python -m spacy download en_core_web_sm
python -m spacy download en_core_web_md
python -m spacy download de_core_news_sm
@allanj
allanj / coref_bert.jsonnet
Created Oct 16, 2019
Coreference with BERT implementation using Latest AllenNLP package (0.9.0)
View coref_bert.jsonnet
local bert_model = "bert-base-uncased";
local train_path = "./datasets/coref/train.english.v4_gold_conll";
local dev_path = "./datasets/coref/dev.english.v4_gold_conll";
local test_path = "./datasets/coref/test.english.v4_gold_conll";
{
"dataset_reader": {
"type": "coref",
"token_indexers": {
"bert": {
View bootstrap_ttest.py
from typing import List, TypeVar, Callable
import numpy as np
T = TypeVar('T')
def bootstrap_paired_ttest(results_a: List[T],
results_b: List[T],
evaluate_func: Callable[[List[T]], float],
sample_times: int = 10000,
View streamlit_demo_usage.py
import streamlit as st
# To make things easier later, we're also importing numpy and pandas for working with sample data.
import numpy
import pandas
# Don't worry, we'll explain this method in the next section. We need to make at least one
# call to Streamlit in order to generate a report.
st.title("Demo Test")
# streamlit.header("I'm a large heading")
# streamlit.subheader("I'm not a large heading")
@allanj
allanj / dep_parse.java
Created Apr 10, 2019
Script for dependency parsing for the dataset
View dep_parse.java
package corenlp.process;
import java.io.BufferedReader;
import java.io.IOException;
import java.io.PrintWriter;
import java.util.ArrayList;
import java.util.List;
import edu.stanford.nlp.ling.CoreLabel;
import edu.stanford.nlp.parser.nndep.DependencyParser;
@allanj
allanj / BIOtoBIOES.py
Last active Mar 31, 2019
Convert the IOB2 tagging scheme to BIOES tagging scheme
View BIOtoBIOES.py
def iob_iobes(tags):
"""
IOB2 (BIO) -> IOBES
"""
new_tags = []
for i, tag in enumerate(tags):
if tag == 'O':
new_tags.append(tag)
elif tag.split('-')[0] == 'B':
if i + 1 != len(tags) and \
@allanj
allanj / iob1toiob2_funct.py
Last active Mar 31, 2019
Convert the tags from IOB1 to IOB2 tagging scheme
View iob1toiob2_funct.py
"""
IOB1: O I I B I
IOB2: O B I B I
"""
from typing import List
def iob2(tags: List[str]):
"""
Check that tags have a valid IOB format.
@allanj
allanj / java_statnlp_print_feature.java
Created Mar 21, 2019
Print the feature string in the StatNLP Java framework (Put to main file)
View java_statnlp_print_feature.java
//main.java
//First of all, after create `GlobalNetworkParam` object.
// run the following code:
GlobalNetworkParam gnp = new GlobalNetworkParam(optimizer, gnnp);
gnp.setStoreFeatureReps();
/************************
After the model has been trained.
model.train(...)
@allanj
allanj / word2vec_bin2txt.py
Created Mar 12, 2019
Convert the word2vec bin file to txt
View word2vec_bin2txt.py
#
# @author: Allan
#
def convert(input, output):
from gensim.models.keyedvectors import KeyedVectors
embedding = KeyedVectors.load_word2vec_format(input, binary=True)
f= open(output, 'w', encoding='utf-8')
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