Update readme

README.md

@@ -27,7 +27,7 @@ Furthermore:
 1. To generate the hidden states for one model `mdl` and all datasets, `cd elk` and then run
 
 ```bash
-python generation_main.py --model deberta-v2-xxlarge-mnli --datasets imdb --prefix normal --device cuda --num_data 1000
+python generation_main.py --model deberta-v2-xxlarge-mnli --datasets imdb --prefix normal --device cuda --num-data 1000
 ```
 
 To test `deberta-v2-xxlarge-mnli` with the misleading prefix, and only the `imdb` and `amazon-polarity` datasets, while printing extra information, run:
@@ -37,12 +37,12 @@ The name of prefix can be found in `./utils_generation/construct_prompts.py`. Th
 1. To train a ccs model and a logistic regression model
 
 ```bash
-python train.py --model deberta-v2-xxlarge-mnli --prefix normal --dataset imdb --num_data 1000
+python train.py --model deberta-v2-xxlarge-mnli --prefix normal --dataset imdb --num-data 1000
 ```
 
 and evaluate:
 ```bash
-python evaluate.py --model deberta-v2-xxlarge-mnli --dataset imdb --num_data 1000
+python evaluate.py --model deberta-v2-xxlarge-mnli --dataset imdb --num-data 1000
 ```
 
 Once finished, results will be saved in `evaluation_results/{model}_{prefix}_{seed}.csv`