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
Download model.safetensors from google-t5/t5-base: direct link, hf CLI and curl.
- Browser
- Download file 892 MB
-
https://huggingface.co/google-t5/t5-base/resolve/main/model.safetensors
- Command line
-
hf download hf://google-t5/t5-base/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/google-t5/t5-base/resolve/main/model.safetensors
892 MB
- Xet hash:
- d56a0dd1b70da7dd7d680239df56a5cf53543d81ab4d92a3584bf673648d7684
- Size of remote file:
- 892 MB
- SHA256:
- a90903540cc02cbeb7ff9f823f1a80eb778c7e22426a0e620b01c77a5ec8f5b4
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