Views
No views yet
.upper() as the model was trained on uppercase tokens.1import torch
2from transformers import MarianMTModel, MarianTokenizer
3
4model_name = "KvaytG/marian-mt-en-ru-informal-caps"
5tokenizer = MarianTokenizer.from_pretrained(model_name)
6model = MarianMTModel.from_pretrained(model_name)
7
8
9def translate(text):
10 input_text = text.upper()
11 inputs = tokenizer(input_text, return_tensors="pt", padding=True)
12 with torch.no_grad():
13 output_tokens = model.generate(**inputs, max_new_tokens=64)
14 return tokenizer.decode(output_tokens[0], skip_special_tokens=True)
15
16
17print(translate("Shut up and look at me!"))
18# Expected: ЗАТКНИСЬ И ПОСМОТРИ НА МЕНЯ!
19
20print(translate("How are you doing today?"))
21# Expected: КАК У ТЕБЯ ДЕЛА СЕГОДНЯ?1@misc{kvaytg_marian_mt_en_ru_informal_caps,
2 author = {KvaytG},
3 title = {MarianMT English-Russian model for informal dialogue in forced uppercase},
4 year = {2026},
5 publisher = {Hugging Face},
6 journal = {Hugging Face Models},
7 url = {https://huggingface.co/KvaytG/marian-mt-en-ru-informal-caps},
8 note = {Fine-tuned from KvaytG/marian-mt-en-ru-high-precision (itself based on Helsinki-NLP/opus-mt-en-ru) for informal/colloquial style with ALL CAPS output.}
9}