Instructions to use nlphuji/mt_coref_en_ru_coref_exp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlphuji/mt_coref_en_ru_coref_exp with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nlphuji/mt_coref_en_ru_coref_exp") model = AutoModelForSeq2SeqLM.from_pretrained("nlphuji/mt_coref_en_ru_coref_exp") - Notebooks
- Google Colab
- Kaggle
ru_coref_all
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-ru on an unknown dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.0
- Tokenizers 0.10.3
- Downloads last month
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