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")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google-t5/t5-base") model = AutoModelForSeq2SeqLM.from_pretrained("google-t5/t5-base") - Inference
- Notebooks
- Google Colab
- Kaggle
Update README.md
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language:
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datasets:
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- c4
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tags:
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- summarization
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- translation
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license: apache-2.0
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```
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See the [Hugging Face T5](https://huggingface.co/docs/transformers/model_doc/t5#transformers.T5Model) docs and a [Colab Notebook](https://colab.research.google.com/github/google-research/text-to-text-transfer-transformer/blob/main/notebooks/t5-trivia.ipynb) created by the model developers for more examples.
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</details>
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language:
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- en
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- ar
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datasets:
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- c4
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tags:
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- summarization
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- translation
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license: apache-2.0
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---
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```
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See the [Hugging Face T5](https://huggingface.co/docs/transformers/model_doc/t5#transformers.T5Model) docs and a [Colab Notebook](https://colab.research.google.com/github/google-research/text-to-text-transfer-transformer/blob/main/notebooks/t5-trivia.ipynb) created by the model developers for more examples.
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</details>
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