readme: ---
  tags:
  - translation
  ---
  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.
  
  ### 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]
  ```