Update README.md

README.md

@@ -54,28 +54,37 @@ Our models are not specifically designed or evaluated for all downstream purpose
 
 ## Usage
 
-### Fine-tuning
 
-Since the released checkpoint is trained with latent pretraining objective, **the outputs are not real actions that are executable in the real world**. To make the model output executable actions, fine-tuning on a small set of trajectories that contain ground-truth actions (~150 trajs) to map the latent action space to the actual action space. 
+### Latent Inference
 
-To finetune the model, run the following command:
+To analyze the output of the model, which is a sequence of latent actions (8^4), run the following command:
 ```bash
-git clone ''
-pip install -r requirements.txt
-./scripts/finetune.sh
+conda create -n lapa python=3.10 -y
+conda activate lapa
+git clone https://github.com/LatentActionPretraining/LAPA.git
+pip install -r requirements.txt 
+mkdir lapa_checkpoints && cd lapa_checkpoints
+wget https://huggingface.co/latent-action-pretraining/LAPA-7B-openx/resolve/main/tokenizer.model
+wget https://huggingface.co/latent-action-pretraining/LAPA-7B-openx/resolve/main/vqgan
+wget https://huggingface.co/latent-action-pretraining/LAPA-7B-openx/resolve/main/params
+cd ..
+python -m latent_pretraining.inference
 ```
 
-### Latent Inference
+### Fine-tuning
 
-To analyze the output of the model, which is a sequence of latent actions (8^4), run the following command:
-To finetune the model, run the following command:
+Since the released checkpoint is trained with latent pretraining objective, **the outputs are not real actions that are executable in the real world**. To make the model output executable actions, fine-tuning on a small set of trajectories that contain ground-truth actions (~150 trajs) to map the latent action space to the actual action space. 
+
+To finetune the model on SIMPLER, run the following command:
 ```bash
-git clone ''
-pip install -r requirements.txt
-./scripts/inference.sh
+./scripts/finetune_simpler.sh
 ```
 
-
+To finetune the model on a custom dataset, run the following command:
+```bash
+python data/finetune_preprocess.py --input_path "/path_to_json_file" --output_filename "data/real_finetune.jsonl" --csv_filename "data/real_finetune.csv"
+./scripts/finetune_real.sh
+```
 
 ## Benchmarks