This is a
microsoft/codebert-base-mlm
model, trained for 1,000,000 steps (with
batch_size=32
) on
C
code from the
codeparrot/github-code-clean
dataset, on the masked-language-modeling task.
@article{zhou2023codebertscore,
url = {https://arxiv.org/abs/2302.05527},
author = {Zhou, Shuyan and Alon, Uri and Agarwal, Sumit and Neubig, Graham},
title = {CodeBERTScore: Evaluating Code Generation with Pretrained Models of Code},
publisher = {arXiv},
year = {2023},
}
Runs of neulab codebert-c on huggingface.co
124
Total runs
0
24-hour runs
11
3-day runs
13
7-day runs
65
30-day runs
More Information About codebert-c huggingface.co Model
codebert-c huggingface.co
codebert-c huggingface.co is an AI model on huggingface.co that provides codebert-c's model effect (), which can be used instantly with this neulab codebert-c model. huggingface.co supports a free trial of the codebert-c model, and also provides paid use of the codebert-c. Support call codebert-c model through api, including Node.js, Python, http.
codebert-c huggingface.co is an online trial and call api platform, which integrates codebert-c's modeling effects, including api services, and provides a free online trial of codebert-c, you can try codebert-c online for free by clicking the link below.
neulab codebert-c online free url in huggingface.co:
codebert-c is an open source model from GitHub that offers a free installation service, and any user can find codebert-c on GitHub to install. At the same time, huggingface.co provides the effect of codebert-c install, users can directly use codebert-c installed effect in huggingface.co for debugging and trial. It also supports api for free installation.