Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-tiny-nl32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-tiny-nl32 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-tiny-nl32") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-tiny-nl32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 674efc54c1f6d956640a85198544259d42ea9877dc122df13147676ab496b097
- Size of remote file:
- 268 MB
- SHA256:
- cbfc675b1ed33e7951d6fbcba26e259423b699819550b808913d1b5a89481445
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