m2m100_418M_ft_ru-kbd_50K
This model is a fine-tuned version of facebook/m2m100_1.2B on the anzorq/ru-kbd dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Eval
predict_bleu = 23.3736
predict_gen_len = 16.8114
predict_loss = 0.9729
predict_runtime = 0:03:29.00
predict_samples = 1034
predict_samples_per_second = 4.947
predict_steps_per_second = 0.211
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0
Inference
pip install transformers sentencepiece
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
model_path = "anzorq/m2m100_1.2B_ft_ru-kbd_50K"
tgt_lang="zu"
tokenizer = AutoTokenizer.from_pretrained('facebook/m2m100_1.2B')
model = AutoModelForSeq2SeqLM.from_pretrained(model_path)
model.to('cuda')
def translate(text, num_beams=4, num_return_sequences=4):
inputs = tokenizer(text, return_tensors="pt")
inputs.to('cuda')
num_return_sequences = min(num_return_sequences, num_beams)
translated_tokens = model.generate(
**inputs,
forced_bos_token_id=tokenizer.lang_code_to_id[tgt_lang],
num_beams=num_beams,
num_return_sequences=num_return_sequences
)
translations = [tokenizer.decode(translation, skip_special_tokens=True) for translation in translated_tokens]
return translations
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