Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-base-nl24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-base-nl24 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-base-nl24") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-base-nl24", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-base-nl24: direct link, hf CLI and curl.
- Browser
- Download file 1.68 GB
-
https://huggingface.co/google/t5-efficient-base-nl24/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-base-nl24/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-base-nl24/resolve/main/flax_model.msgpack
1.68 GB
- Xet hash:
- 4ef66b353a66aa3d222b043856cf78dfb5e6c39ec4f9cd9da245575ad8856dcc
- Size of remote file:
- 1.68 GB
- SHA256:
- 235abb7bf341c4ec942c65a71555d9e4a496de89a08fc8c539dfdf776f3616c4
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