README.md

---
library_name: sample-factory
tags:
- deep-reinforcement-learning
- reinforcement-learning
- sample-factory
model-index:
- name: APPO
  results:
  - task:
      type: reinforcement-learning
      name: reinforcement-learning
    dataset:
      name: doom_deadly_corridor
      type: doom_deadly_corridor
    metrics:
    - type: mean_reward
      value: 8.92 +/- 7.43
      name: mean_reward
      verified: false
---

An **APPO** model trained on the **doom_deadly_corridor** environment.

This model was trained using Sample-Factory 2.1.1


## Downloading the model

After installing Sample-Factory, download the model with:
```
python -m sample_factory.huggingface.load_from_hub -r elliemci/deadly_corridor_experiment
```

    
## Using the model

To run the model after download, use the `enjoy` script corresponding to this environment:
```
python -m <path.to.enjoy.module> --algo=APPO --env=doom_deadly_corridor --train_dir=./train_dir --experiment=deadly_corridor_experiment
```
    
## Training with this model

To continue training with this model, use the `train` script corresponding to this environment:
```
python -m <path.to.train.module> --algo=APPO --env=doom_deadly_corridor --train_dir=./train_dir --experiment=deadly_corridor_experiment --restart_behavior=resume --train_for_env_steps=10000000000
```