Translation
Transformers
Safetensors
English
Vietnamese
umt5
text2text-generation
biomedical
en-vimedner
Instructions to use nhuvo/umt5-base-en-vimedner-mt-en2vi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nhuvo/umt5-base-en-vimedner-mt-en2vi 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="nhuvo/umt5-base-en-vimedner-mt-en2vi")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nhuvo/umt5-base-en-vimedner-mt-en2vi") model = AutoModelForSeq2SeqLM.from_pretrained("nhuvo/umt5-base-en-vimedner-mt-en2vi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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