YAML Metadata
Warning:
empty or missing yaml metadata in repo card
(https://huggingface.co/docs/hub/model-cards#model-card-metadata)
How to use
import logging
from simpletransformers.seq2seq import Seq2SeqModel, Seq2SeqArgs
logging.basicConfig(level=logging.INFO)
transformers_logger = logging.getLogger("transformers")
transformers_logger.setLevel(logging.WARNING)
model_args = Seq2SeqArgs()
# 加载本地训练好的模型
model = Seq2SeqModel(
encoder_decoder_type="bart",
encoder_decoder_name="NTUYG/SOTitle-java-BART",
args=model_args,
)
describe = """
I am a beginner at Android Java development but I have a few years of school + uni experience in Java. I am trying to write to a text file in an assets folder in my app using FileOutputStream but it doesn't seem to write to it at all since I am using InputStream to read the file after and there haven't any updates. Here is my code
"""
code = """
private void updateTextFile(String update) {
FileOutputStream fos = null;
try
{
fos = openFileOutput("Questions",MODE_PRIVATE);
fos.write("Testing".getBytes());
}
catch (FileNotFoundException e)
{
e.printStackTrace();
}
catch (IOException e)
{
e.printStackTrace();
}
finally
{
if(fos!=null)
{
try
{
fos.close();
}
catch (IOException e)
{
e.printStackTrace();
}
}
}
String text = "";
try
{
InputStream is = getAssets().open("Questions");
int size = is.available();
byte[] buffer = new byte[size];
is.read(buffer);
is.close();
text = new String(buffer);
}
catch (IOException e)
{
e.printStackTrace();
}
System.out.println("Tesing output " + text);
}
"""
from nltk import word_tokenize
describe = describe.replace('\n',' ').replace('\r',' ')
describe = ' '.join(word_tokenize(describe))
code = code.replace('\n',' ').replace('\r',' ')
code = ' '.join(word_tokenize(code))
# human : Java Android Cant seem to update text file using FileOutputStream
body = describe + ' <code> ' + code +' </code>'
print(
model.predict(
[
body
]
)
)
- Downloads last month
- 28
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.