Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-small-el16-dl2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-small-el16-dl2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-small-el16-dl2") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-small-el16-dl2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-small-el16-dl2: direct link, hf CLI and curl.
- Browser
- Download file 301 MB
-
https://huggingface.co/google/t5-efficient-small-el16-dl2/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-small-el16-dl2/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-small-el16-dl2/resolve/main/flax_model.msgpack
301 MB
- Xet hash:
- 182992ff1e6d6ec4ed59e827c0b3bf4287c69d3d2eda77931c4461c87542de9f
- Size of remote file:
- 301 MB
- SHA256:
- 3cd213fadef10334b8d9b68e53c82bf91b96dd1938b7453a4f16f7e6943ce521
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