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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google-t5/t5-small") model = AutoModelForSeq2SeqLM.from_pretrained("google-t5/t5-small", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from google-t5/t5-small: direct link, hf CLI and curl.
- Browser
- Download file 1.39 MB
-
https://huggingface.co/google-t5/t5-small/resolve/main/tokenizer.json
- Command line
-
hf download hf://google-t5/t5-small/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/google-t5/t5-small/resolve/main/tokenizer.json
1.39 MB
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