Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-large-dl8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-large-dl8 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-large-dl8") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-large-dl8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-large-dl8: direct link, hf CLI and curl.
- Browser
- Download file 1.88 GB
-
https://huggingface.co/google/t5-efficient-large-dl8/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-large-dl8/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-large-dl8/resolve/main/flax_model.msgpack
1.88 GB
- Xet hash:
- 8f0e4a2ac4f69c1e855576837c5e27a8d6a8f607bc66b6d978dad2cf08db34ea
- Size of remote file:
- 1.88 GB
- SHA256:
- bc8bd632d603cb28643d01e68189c91dfd6c03090a96248e673709959e6c5533
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