Update README.md

Added usage example

README.md

@@ -4,4 +4,28 @@ tags:
 ---
 This model translate from English to Khmer.
 It is the pure fine-tuned version of MarianMT model en-zh.
-This is the result after 30 epochs of pure fine-tuning of khmer language.
+This is the result after 30 epochs of pure fine-tuning of khmer language.
+
+### Example
+```
+%%capture
+!pip install transformers transformers[sentencepiece]
+
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+# Download the pretrained model for English-Vietnamese available on the hub
+model = AutoModelForSeq2SeqLM.from_pretrained("CLAck/en-km")
+
+tokenizer = AutoTokenizer.from_pretrained("CLAck/en-km")
+# Download a tokenizer that can tokenize English since the model Tokenizer doesn't know anymore how to do it
+# We used the one coming from the initial model
+# This tokenizer is used to tokenize the input sentence
+tokenizer_en = AutoTokenizer.from_pretrained('Helsinki-NLP/opus-mt-en-zh')
+# These special tokens are needed to reproduce the original tokenizer
+tokenizer_en.add_tokens(["<2zh>", "<2khm>"], special_tokens=True)
+
+sentence = "The cat is on the table"
+# This token is needed to identify the target language
+input_sentence = "<2khm> " + sentence 
+translated = model.generate(**tokenizer_en(input_sentence, return_tensors="pt", padding=True))
+output_sentence = [tokenizer.decode(t, skip_special_tokens=True) for t in translated]
+```