Instructions to use inseq/wmt21-mlqe-ru-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use inseq/wmt21-mlqe-ru-en with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="inseq/wmt21-mlqe-ru-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("inseq/wmt21-mlqe-ru-en") model = AutoModelForSeq2SeqLM.from_pretrained("inseq/wmt21-mlqe-ru-en") - Notebooks
- Google Colab
- Kaggle
Fairseq Ru-En NMT WMT20 MLQE
This repository contains the Russian-English model trained with the fairseq toolkit that was used to produce translations used in the WMT21 shared task on quality estimation (QE) on the MLQE dataset.
The checkpoint was converted from the original fairseq checkpoint available here using the convert_fsmt_original_pytorch_checkpoint_to_pytorch.py script from the 🤗 Transformers library (v4.26.0).
Please refer to the repositories linked above for additional information on usage, parameters and training data.
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