Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-large-dl16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-large-dl16 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-large-dl16") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-large-dl16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-large-dl16: direct link, hf CLI and curl.
- Browser
- Download file 2.41 GB
-
https://huggingface.co/google/t5-efficient-large-dl16/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-large-dl16/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-large-dl16/resolve/main/flax_model.msgpack
2.41 GB
- Xet hash:
- ddfc8ddbf4a6ca242c9a8f5399db38941e6f0955ac9562dab0feeba7fa5ce067
- Size of remote file:
- 2.41 GB
- SHA256:
- f7399413300ff379dd4c9905ba963a31480533710ca09d6e9ceae32e7574aa1c
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