Update README.md

README.md

@@ -15,4 +15,34 @@ library_name: transformers
 This is fine tuned NLLB-200 model for Chechen-Russian translation, presented in paper [The first open machine translation system for the Chechen language](https://www.arxiv.org/abs/2507.12672).
 
 
-Language token for the Chechen language is `ce_Cyrl`.
+The language token for the Chechen language is `ce_Cyrl`, while for all the other languages included in NLLB-200, the tokens are composed of three letters (i.e. rus_Cyrl for Russian).
+
+Here is an example of how the model can be used in the code:
+
+```python
+import torch
+from transformers import AutoModelForSeq2SeqLM
+from transformers import NllbTokenizer
+
+model_nllb = AutoModelForSeq2SeqLM.from_pretrained('NM-development/nllb-ce-rus-v0').cuda()
+tokenizer_nllb = NllbTokenizer.from_pretrained('NM-development/nllb-ce-rus-v0')
+
+def translate(text, model, tokenizer, src_lang='rus_Cyrl', tgt_lang='eng_Latn', a=16, b=1.5, max_input_length=1024, **kwargs):
+    model.eval()
+    with torch.no_grad():
+        tokenizer.src_lang = src_lang
+        tokenizer.tgt_lang = tgt_lang
+        inputs = tokenizer(text, return_tensors='pt', padding=True, truncation=True, max_length=max_input_length)
+        result = model.generate(
+            **inputs.to(model.device),
+            forced_bos_token_id=tokenizer.convert_tokens_to_ids(tgt_lang),
+            max_new_tokens=int(a + b * inputs.input_ids.shape[1]),
+            **kwargs
+        )
+    return tokenizer.batch_decode(result, skip_special_tokens=True)
+
+
+text = "Стигална кӀел къахьоьгуш, ша мел динчу хӀуманах буьсун болу хӀун пайда оьцу адамо?"
+translate(text, model_nllb, tokenizer_nllb, src_lang='ce_Cyrl', tgt_lang='rus_Cyrl')[0]
+# 'Что пользы человеку от того, что он трудился под солнцем и что сделал?'
+```