Translation
Transformers
PyTorch
TensorFlow
JAX
Rust
ONNX
Safetensors
t5
text2text-generation
summarization
text-generation-inference
Instructions to use google-t5/t5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google-t5/t5-small 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="google-t5/t5-small")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google-t5/t5-small") model = AutoModelForSeq2SeqLM.from_pretrained("google-t5/t5-small") - Inference
- Notebooks
- Google Colab
- Kaggle
Datasets used to train NMT supervised task ?
#25
by OrianeN - opened
If I understood the paper correctly, the T5-small was trained on supervised tasks including NMT in 3 directions: EN>FR, EN>RO and EN>DE.
Yet I can't find the datasets used to train on these supervised tasks, could you please add them to the model card ?
If I'm not mistaken, the paper mentions the following training datasets for the NMT tasks:
- EN>DE: News Commentary v13, Common Crawl, Europarl v7 (+ newstest2013 for validation)
- EN>FR: WMT 2015 (+ newstest2014 for validation)
- EN>RO: WMT 2016