basic example

README.md

@@ -14,6 +14,27 @@ Intended Examples:
 
 People's names, gender pronouns, gendered words (father, mother), and many other values are currently unchanged by this model. Future versions may be trained on more data.
 
+## Sample Code
+
+```
+import torch
+from transformers import AutoTokenizer, EncoderDecoderModel
+
+model = EncoderDecoderModel.from_encoder_decoder_pretrained(
+  "monsoon-nlp/ar-seq2seq-gender-encoder",
+  "monsoon-nlp/ar-seq2seq-gender-decoder",
+  min_length=40
+)
+tokenizer = AutoTokenizer.from_pretrained('monsoon-nlp/ar-seq2seq-gender-decoder') # same as MARBERT original
+
+input_ids = torch.tensor(tokenizer.encode("أنا سعيدة")).unsqueeze(0)
+generated = model.generate(input_ids, decoder_start_token_id=model.config.decoder.pad_token_id)
+tokenizer.decode(generated.tolist()[0][1 : len(input_ids[0]) - 1])
+> 'انا سعيد'
+```
+
+https://colab.research.google.com/drive/1S0kE_2WiV82JkqKik_sBW-0TUtzUVmrV?usp=sharing
+
 ## Training
 
 I originally developed