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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
```
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