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 # 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
+```
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