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") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a4fbde784fb853487c6d5ba0940d53b066fa2646778299a74fb89d6a7e8db40
- Size of remote file:
- 242 MB
- SHA256:
- b143e13ccb7307ad36b3327ca49019f222606e945d9b995404d7200224504a9c
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