Update README.md

README.md

@@ -25,32 +25,4 @@ A(n) **APPO** model trained on the **atari_carnival** environment.
 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 ksridhar/atari_2B_atari_carnival_1111
-```
-
-    
-## 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=atari_carnival --train_dir=./train_dir --experiment=atari_2B_atari_carnival_1111
-```
-
-
-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 <path.to.train.module> --algo=APPO --env=atari_carnival --train_dir=./train_dir --experiment=atari_2B_atari_carnival_1111 --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.