Translation
Transformers
PyTorch
TensorFlow
JAX
Rust
Safetensors
t5
text2text-generation
summarization
text-generation-inference
Instructions to use google-t5/t5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google-t5/t5-base 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-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google-t5/t5-base") model = AutoModelForSeq2SeqLM.from_pretrained("google-t5/t5-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Use T5ForConditionalGeneration (#8)
- Use T5ForConditionalGeneration (6421ace5cab13343b167e259b63b7608bb2a40bf) Co-authored-by: Félix Marty <fxmarty@users.noreply.huggingface.co>a4986ab
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