Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-small-dl16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-small-dl16 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-small-dl16") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-small-dl16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-small-dl16: direct link, hf CLI and curl.
- Browser
- Download file 410 MB
-
https://huggingface.co/google/t5-efficient-small-dl16/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-small-dl16/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-small-dl16/resolve/main/flax_model.msgpack
410 MB
- Xet hash:
- 35a4977f5d9e4babaeacbdfe29d9322bb9c1a43cb999d349e8959aec77e1f3d7
- Size of remote file:
- 410 MB
- SHA256:
- 36becf15060a93a11ca277458147e09e2bb1aaf4d56183fde2b05ba54bbaa403
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