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ru-mbart-large-summ

Model

Model forked from ru-bart-large which is smaller version of the facebook/mbart-large-50 with only Russian and English embeddings.

Data

All 'train' subsets was concatenated and shuffled with seed 1000 - 7.

Train subset = 155678 rows.

Metrics

Evaluation on 10% of concatenated 'validation' subsets = 1458 rows.

See WandB logs.

See report at REPORT WIP.

Usage

from transformers import pipeline


pipe = pipeline('summarization', model='d0rj/ru-mbart-large-summ')
pipe(text)
import torch
from transformers import AutoTokenizer, MBartModel


tokenizer = AutoTokenizer.from_pretrained('d0rj/ru-mbart-large-summ')
model = MBartModel.from_pretrained('d0rj/ru-mbart-large-summ')

inputs = tokenizer('Всё в порядке, мимо двигал Утром прозвенел будильник', return_tensors='pt')
with torch.no_grad():
    outputs = model(**inputs)

last_hidden_states = outputs.last_hidden_state
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Model size
380M params
Tensor type
F32
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