Introduction of SOCO-Java-CodeBERTa-MNRL-Triplets-100
Model Details of SOCO-Java-CodeBERTa-MNRL-Triplets-100
SentenceTransformer based on huggingface/CodeBERTa-small-v1
This is a
sentence-transformers
model finetuned from
huggingface/CodeBERTa-small-v1
on the
soco_train_java
dataset. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
for ( char ch2 = 'A'; ch2 <= 'z'; ch2++ )
{
if (ch2>'Z' && ch2<'a')
{
...
import java.net.
;
import java.io.
;
import java.util.Date;
public class Dictionary{
private static String password=" ";
public static void main(String[] args) {
String Result="";
if (args.length<1)
{
System.out.println("Correct Format Filename username e.g<>");
System.exit(1);
}
Dictionary dicton1 = new Dictionary();
Result=dicton1.Dict("
http://sec-crack.cs.rmit.edu./SEC/2/",args[0]
);
System.out.println("Cracked Password for The User "+args[0]+" The Password is.."+Result);
public class RunnableHttpRequest extends Thread
{
protected String targetURL = "
http://localhost:8080/
";
protected int requestCount = 1;
protected ArrayList timingList = new ArrayList();
protected HttpRequestClient req;
Boolean finished = new Boolean(false);
HttpRequestThreadPool pool;
public void run()
{
try
{
for (int i = 0; i < getRequestCount() && !getFinished().booleanValue(); i++)
{
try
{
req =
new HttpRequestClient(getTargetURL());
public class Dictionary {
public static BufferedReader in;
public static void main(String[] args) throws Exception {
String baseURL = "
http://sec-crack.cs.rmit.edu./SEC/2/index.php
";
int count=0;
Date date = new Date();
startTime=date.getTime();
int LIMITINMINUTES=45;
int TIMELIMIT=LIMITINMINUTES
1000*60;
boolean timedOut=false;
boolean found=false;
Vector dictionary=new Vector(readWords());
System.out.println("Words in dictionary: "+dictionary.size());
while (found==false && timedOut==false && dictionary.elementAt(count)!=null) {
Date endDate = new Date();
endTime=endDate.getTime();
if (endTime>(TIMELIMIT+startTime)){
System.out.println("Timed out");
timedOut=true;
}
@inproceedings{reimers-2019-sentence-bert,
title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
author = "Reimers, Nils and Gurevych, Iryna",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
month = "11",
year = "2019",
publisher = "Association for Computational Linguistics",
url = "https://arxiv.org/abs/1908.10084",
}
MultipleNegativesRankingLoss
@misc{henderson2017efficient,
title={Efficient Natural Language Response Suggestion for Smart Reply},
author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
year={2017},
eprint={1705.00652},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Runs of buelfhood SOCO-Java-CodeBERTa-MNRL-Triplets-100 on huggingface.co
136
Total runs
15
24-hour runs
28
3-day runs
28
7-day runs
45
30-day runs
More Information About SOCO-Java-CodeBERTa-MNRL-Triplets-100 huggingface.co Model
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SOCO-Java-CodeBERTa-MNRL-Triplets-100 is an open source model from GitHub that offers a free installation service, and any user can find SOCO-Java-CodeBERTa-MNRL-Triplets-100 on GitHub to install. At the same time, huggingface.co provides the effect of SOCO-Java-CodeBERTa-MNRL-Triplets-100 install, users can directly use SOCO-Java-CodeBERTa-MNRL-Triplets-100 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
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