metadata
license: mit
widget: null
language:
- en
datasets:
- pytorrent
🔥 RoBERTa-MLM-based PyTorrent 1M 🔥
Pretrained weights based on PyTorrent Dataset which is a curated data from a large official Python packages. We use PyTorrent dataset to train a preliminary DistilBERT-Masked Language Modeling(MLM) model from scratch. The trained model, along with the dataset, aims to help researchers to easily and efficiently work on a large dataset of Python packages using only 5 lines of codes to load the transformer-based model. We use 1M raw Python scripts of PyTorrent that includes 12,350,000 LOC to train the model. We also train a byte-level Byte-pair encoding (BPE) tokenizer that includes 56,000 tokens, which is truncated LOC with the length of 50 to save computation resources.
Training Objective
This model is trained with a Masked Language Model (MLM) objective.
How to use the model?
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("Fujitsu/pytorrent")
model = AutoModel.from_pretrained("Fujitsu/pytorrent")