Instructions to use CLAck/en-vi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLAck/en-vi 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="CLAck/en-vi")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("CLAck/en-vi") model = AutoModelForSeq2SeqLM.from_pretrained("CLAck/en-vi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): c715352
Create README.md
Browse files
README.md
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---
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language:
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- en
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- vi
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tags:
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- translation
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license: apache-2.0
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datasets:
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- ALT
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metrics:
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- sacrebleu
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---
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This is a finetuning of a MarianMT pretrained on English-Chinese. The target language pair is English-Vietnamese.
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The first phase of training (mixed) is performed on a dataset containing both English-Chinese and English-Vietnamese sentences.
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The second phase of training (pure) is performed on a dataset containing only English-Vietnamese sentences.
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### Training results
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MIXED
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| Epoch | Bleu |
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|:-----:|:-------:|
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| 1.0 | 26.2407 |
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| 2.0 | 32.6016 |
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| 3.0 | 35.4060 |
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| 4.0 | 36.6737 |
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| 5.0 | 37.3774 |
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PURE
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| Epoch | Bleu |
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|:-----:|:-------:|
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| 1.0 | 37.3169 |
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| 2.0 | 37.4407 |
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| 3.0 | 37.6696 |
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| 4.0 | 37.8765 |
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| 5.0 | 38.0105 |
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