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README.md

@@ -30,7 +30,7 @@ Documentation for how to use Sample-Factory can be found at https://www.samplefa
 
 After installing Sample-Factory, download the model with:
 ```
-python -m sample_factory.huggingface.load_from_hub -r caioiglesias/rl_course_vizdoom_health_gathering_supreme
+python -m sample_factory.huggingface.load_from_hub -r Gyaneshere/doom_health_gathering_supreme
 ```
 
     
@@ -38,7 +38,7 @@ python -m sample_factory.huggingface.load_from_hub -r caioiglesias/rl_course_viz
 
 To run the model after download, use the `enjoy` script corresponding to this environment:
 ```
-python -m .usr.local.lib.python3.8.dist-packages.ipykernel_launcher --algo=APPO --env=doom_health_gathering_supreme --train_dir=./train_dir --experiment=rl_course_vizdoom_health_gathering_supreme
+python -m .usr.local.lib.python3.8.dist-packages.ipykernel_launcher --algo=APPO --env=doom_health_gathering_supreme --train_dir=./train_dir --experiment=doom_health_gathering_supreme
 ```
 
 
@@ -49,7 +49,7 @@ See https://www.samplefactory.dev/10-huggingface/huggingface/ for more details
 
 To continue training with this model, use the `train` script corresponding to this environment:
 ```
-python -m .usr.local.lib.python3.8.dist-packages.ipykernel_launcher --algo=APPO --env=doom_health_gathering_supreme --train_dir=./train_dir --experiment=rl_course_vizdoom_health_gathering_supreme --restart_behavior=resume --train_for_env_steps=10000000000
+python -m .usr.local.lib.python3.8.dist-packages.ipykernel_launcher --algo=APPO --env=doom_health_gathering_supreme --train_dir=./train_dir --experiment=doom_health_gathering_supreme --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.