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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44b06e73cdc144d094fb49a9039a078f31def875ed7a346a19ccbb05ef397c90
- Size of remote file:
- 1.94 GB
- SHA256:
- c390b961c4d0f75f6692f058d372a825b0cba41e85642cf06a5187a3c7b3b6b9
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