Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-large-nh24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-large-nh24 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-large-nh24") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-large-nh24", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-large-nh24: direct link, hf CLI and curl.
- Browser
- Download file 3.55 GB
-
https://huggingface.co/google/t5-efficient-large-nh24/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-large-nh24/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-large-nh24/resolve/main/flax_model.msgpack
3.55 GB
- Xet hash:
- 02d9e3f5a90d1e0397aea074f9073be8288fcc4406abc49adc26ba6db76c2644
- Size of remote file:
- 3.55 GB
- SHA256:
- d8b03a3c16a870f3d43346583def642cad17fb8ab564a1a2eccfb2e7fcb53d84
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