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")# 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 model.safetensors from google-t5/t5-small: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/google-t5/t5-small/resolve/main/model.safetensors
- Command line
-
hf download hf://google-t5/t5-small/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/google-t5/t5-small/resolve/main/model.safetensors
242 MB
- Xet hash:
- 5b8bfc2f6adc7a5f097f02d2f09acc4572525485014bdf8f475fe1154bf7e838
- Size of remote file:
- 242 MB
- SHA256:
- bd944e5f1b3ad9b70dd9d00010a517059e19265671076b8b0a4a58d9491842bc
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