Translation
Transformers
PyTorch
TensorFlow
Safetensors
t5
text-generation
summarization
text-generation-inference
Instructions to use google-t5/t5-3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google-t5/t5-3b 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/t5-3b")# Load model directly from transformers import AutoTokenizer, AutoModelWithLMHead tokenizer = AutoTokenizer.from_pretrained("google-t5/t5-3b") model = AutoModelWithLMHead.from_pretrained("google-t5/t5-3b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 530469fe38ce63c5b1ac30aabb96feb9e848addba11ee4bb54fb165058b31033
- Size of remote file:
- 11.4 GB
- SHA256:
- 85e93c65d8bc96cdc8dcdc164f371f041e4e34961f3f3c06a418309ee1203391
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