Create README.md
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README.md
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---
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license: mit
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widget:
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language:
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- en
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datasets:
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- pytorrent
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---
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# 🔥 RoBERTa-MLM-based PyTorrent 1M 🔥
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Pretrained weights based on [PyTorrent Dataset](https://github.com/fla-sil/PyTorrent) which is a curated data from a large official Python packages.
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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.
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### Training Objective
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This model is trained with a Masked Language Model (MLM) objective.
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## How to use the model?
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```python
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained("Fujitsu/pytorrent")
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model = AutoModel.from_pretrained("Fujitsu/pytorrent")
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```
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