Translation
Transformers
PyTorch
TensorFlow
JAX
Safetensors
t5
text2text-generation
summarization
text-generation-inference
Instructions to use google-t5/t5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google-t5/t5-large 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-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google-t5/t5-large") model = AutoModelForSeq2SeqLM.from_pretrained("google-t5/t5-large", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 25c691baf5743cc129bd1385f7c71a826b9e808ad4e63e7189fa071e8680a84e
- Size of remote file:
- 2.95 GB
- SHA256:
- bb566a699a6939ffa2ac2fa7eb26fd02b13d4d14956186d7af1e46ce19c67d32
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