Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-small-ff12000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-small-ff12000 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-small-ff12000") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-small-ff12000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-small-ff12000: direct link, hf CLI and curl.
- Browser
- Download file 745 MB
-
https://huggingface.co/google/t5-efficient-small-ff12000/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-small-ff12000/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-small-ff12000/resolve/main/flax_model.msgpack
745 MB
- Xet hash:
- debafc25ad0aafad4e6d5b862c0f1e869427112ee890403105fdfccc8750665e
- Size of remote file:
- 745 MB
- SHA256:
- 16a102fd1d40ea4c8142c69322908b3b87b89f88d34479cef0e60db32d1b6448
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