diff --git a/README.md b/README.md
index 98658fb..c1e114a 100644
--- a/README.md
+++ b/README.md
@@ -1,19 +1,2 @@
-# Inst2Vec
-Using 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
-```
+# Inst2Vec Model
+Using HuggingFace Transformers to train a BERT for Assemble Language