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README.md

@@ -15,11 +15,42 @@ model-index:
       type: Ant
     metrics:
     - type: mean_reward
-      value: 11830.10 +/- 875.26
+      value: 11827.40 +/- 1185.26
       name: mean_reward
       verified: false
 ---
 
 A(n) **APPO** model trained on the **Ant** environment.
-This model was trained using Sample Factory 2.0: https://github.com/alex-petrenko/sample-factory
-    
+
+This model was trained using Sample-Factory 2.0: https://github.com/alex-petrenko/sample-factory.
+Documentation for how to use Sample-Factory can be found at https://www.samplefactory.dev/
+
+
+**Downloading the model**
+
+After installing Sample-Factory, download the model with:
+```
+python -m sample_factory.huggingface.load_from_hub -r andrewzhang505/isaacgym_ant
+```
+
+    
+**Using the model**
+
+To run the model after download, use the `enjoy` script corresponding to this environment:
+```
+python -m sf_examples.isaacgym_examples.enjoy_isaacgym --algo=APPO --env=Ant --train_dir=./train_dir --experiment=isaacgym_ant
+```
+
+
+You can also upload models to the Hugging Face Hub using the same script with the `--push_to_hub` flag.
+See https://www.samplefactory.dev/10-huggingface/huggingface/ for more details
+        
+**Training with this model**
+
+To continue training with this model, use the `train` script corresponding to this environment:
+```
+python -m sf_examples.isaacgym_examples.train_isaacgym --algo=APPO --env=Ant --train_dir=./train_dir --experiment=isaacgym_ant --restart_behavior=resume --train_for_env_steps=10000000000
+```
+
+Note, you may have to adjust `--train_for_env_steps` to a suitably high number as the experiment will resume at the number of steps it concluded at.
+