Update README.md

README.md

@@ -20,6 +20,17 @@ from transformers import AutoConfig, AutoModel
 
 config = AutoConfig.from_pretrained("amaye15/autoencoder", trust_remote_code = True)
 
+# Let's say you want to change the input_dim and latent_dim
+config.input_dim = 1024  # New input dimension
+config.latent_dim = 64   # New latent dimension
+
+# Similarly, update other parameters as needed
+config.layer_types = 'gru'  # Change layer types to 'gru'
+config.dropout_rate = 0.2   # Update dropout rate
+config.num_layers = 4       # Change the number of layers
+config.compression_rate = 0.6  # Update compression rate
+config.bidirectional = False   # Change to unidirectional
+
 ### Change Configuration
 
 model = AutoModel.from_config(config, trust_remote_code = True)
@@ -31,16 +42,12 @@ input_data = torch.rand((32, 10, 784))  # Adjust shape according to your needs
 with torch.no_grad():  # Assuming inference only
     output = model(input_data)
 
-
-
 ### To-Do
 # The `output` is a dictionary with 'encoder_final' and 'decoder_final' keys
-encoded_representation = output['encoder_final']
-reconstructed_data = output['decoder_final']
+# encoded_representation = output['encoder_final']
+# reconstructed_data = output['decoder_final']
 ```
 
-Replace `your_model_directory` with the actual path where your `AutoEncoder` and `AutoEncoderConfig` classes are located.
-
 ## Training Data
 *Omitted - to be filled in with details about the training data used for the model.*