Instructions to use transZ/M2M_Vi_Ba with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use transZ/M2M_Vi_Ba 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="transZ/M2M_Vi_Ba")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("transZ/M2M_Vi_Ba") model = AutoModelForSeq2SeqLM.from_pretrained("transZ/M2M_Vi_Ba") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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# How to run the model
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```python
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from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
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---
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language:
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- vi
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- ba
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tags:
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- translation
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datasets:
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- custom dataset
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metrics:
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- bleu
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- sacrebleu
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---
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# How to run the model
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```python
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from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
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