Added an example of use

README.md

@@ -5,6 +5,24 @@ license: mit
 
 The MADLAD-400 model fine-tuned to translate from Proper Karelian, Livvi, Ludian, and Veps to Russian and vice versa. We call this model **Pa**ragraph-**Le**vel as we trained it on paragraphs comprising multiple sentences. The model demonstrates the capacity to handle gender-neutral pronouns (presenting a major obstacle in translating from Finno-Ugric languages) and other discourse-level phenomena.
 
+### Example Usage for Inference
+
+````
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+model = AutoModelForSeq2SeqLM.from_pretrained('tartuNLP/pale-madlad-mt')
+tokenizer = AutoTokenizer.from_pretrained('tartuNLP/pale-madlad-mt')
+
+# You need to explicitly prepend a target language tag to the input string in the format <2xx>, where xx stands for the language code.
+# Language codes: 'krl' for Proper Karelian, 'lud' for Ludian, 'olo' for Livvi, 'vep' for Veps, 'ru' for Russian, 'en' for English.
+text = '<2krl>' + 'Здравствуйте!'
+
+inputs = tokenizer(text, return_tensors='pt').input_ids
+outputs = model.generate(inputs)
+tokenizer.decode(outputs[0], skip_special_tokens=True)
+# Output: Terveh!
+````
+
 Please cite the following paper if you use this model in your work:
 ```
 @inproceedings{