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# Inst2Vec Model # Inst2Vec Model
Using HuggingFace Transformers to train a BERT for Assemble Language Using [HuggingFace Transformers](https://github.com/huggingface/transformers) to train a BERT for Assemble Language from scratch. We name it `Inst2Vec` for it is designed to generate vectors for assemble instructions.
It is a part of the model we proposed in the paper [A Hierarchical Graph-based Neural Network for Malware Classification]().
The preprocessing procedure can be found in [process_data](./process_data/readme.md).
You can simply run `python train_my_tokenizer.py` to obtain an Assemble Tokenizer.
The script I use to train the `Inst2Vec1` model is as follows:
```
python my_run_mlm_no_trainer.py \
--per_device_train_batch_size 8192 \
--per_device_eval_batch_size 16384 \
--num_warmup_steps 4000 --output_dir ./ \
--seed 1234 --preprocessing_num_workers 32 \
--max_train_steps 150000 \
--eval_every_steps 1000
```