Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-mini-nl6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-mini-nl6 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-mini-nl6") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-mini-nl6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-mini-nl6: direct link, hf CLI and curl.
- Browser
- Download file 163 MB
-
https://huggingface.co/google/t5-efficient-mini-nl6/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-mini-nl6/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-mini-nl6/resolve/main/flax_model.msgpack
163 MB
- Xet hash:
- 85da909d39aba9a438cfa6863dfddc1a425fd9a84255933dbfab4a1b91be0d4e
- Size of remote file:
- 163 MB
- SHA256:
- 25aeb72ddf86cc18a8e529666f117be72b8054e683e2ce4132ee4d12c28877c6
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