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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download rust_model.ot from google-t5/t5-base: direct link, hf CLI and curl.
- Browser
- Download file 892 MB
-
https://huggingface.co/google-t5/t5-base/resolve/refs%2Fpr%2F32/rust_model.ot
- Command line
-
hf download hf://google-t5/t5-base@refs/pr/32/rust_model.ot
-
curl -L -o rust_model.ot https://huggingface.co/google-t5/t5-base/resolve/refs%2Fpr%2F32/rust_model.ot
892 MB
- Xet hash:
- 1fa8ec2fa1f15a8ebd39d742f3d05b72191c321cd9bc18642f67574a365667fe
- Size of remote file:
- 892 MB
- SHA256:
- d53fb0a3dbc251585dc6d863e8be405128b7d426ac860b9fc26ecefbcc88afeb
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