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Fix Readme, fix Timer in training

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Starrick
2025-09-09 15:04:00 +08:00
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workspace/README.md
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This document explains the key configuration parameters that can be modified for Wall-X training.
## Quick Start Checklist
1. **Update run.sh**: Set `code_dir` and `config_path` to your actual paths
2. **Configure GPUs**: Set `CUDA_VISIBLE_DEVICES` for your available GPUs
3. **Update config paths**: Replace all `/path/to/` placeholders in `config_qact.yml` with actual paths
4. **Configure robot**: Set `dof_config` and `agent_pos_config` for your robot
5. **Set dataset**: Choose appropriate `repo_id` for your dataset
6. **Adjust batch size**: Set `batch_size_per_gpu` based on GPU memory
7. **Run training**: Execute `bash ./workspace/lerobot_example/run.sh`
## Enable FAST tokenizer
To fine-tune using the FAST tokenizer, please download the repository and update the `action_tokenizer_path`. Make sure to set `use_fast_tokenizer` to `true`:
```bash
git clone https://huggingface.co/physical-intelligence/fast
```
## Quick Start Checklist
1. **Update run.sh**: Set `code_dir` and `config_path` to your actual paths
2. **Configure GPUs**: Set `CUDA_VISIBLE_DEVICES` for your available GPUs
3. **Update config paths**: Replace all `/path/to/` placeholders in config.yml with actual paths
4. **Configure robot**: Set `dof_config` and `agent_pos_config` for your robot
5. **Set dataset**: Choose appropriate `repo_id` for your dataset
6. **Adjust batch size**: Set `batch_size_per_gpu` based on GPU memory
7. **Run training**: Execute `bash ./workspace/lerobot_example/run.sh`
## Required Paths (Must Modify)
```yaml
processor_path: "/path/to/model/" # Path to model processor
pretrained_qwen_vl_path: "/path/to/qwen_vl_model/" # Path to pretrained Qwen VL model
qwen_vl_act_config_path: "/path/to/config.json" # Path to model config file
pretrained_wallx_path: "/path/to/wallx_model/" # Path to pretrained Qwen VL model
use_fast_tokenizer: false # True: train FAST, False: train Flow
action_tokenizer_path: "/path/to/fast/" # Path to action tokenizer
save_path: "/path/to/workspace/" # Path to save training outputs
save_path: "/path/to/workspace/" # Path to save training outputs
```
## Training Parameters (Commonly Modified)