Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-small-nl48 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-small-nl48 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-small-nl48") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-small-nl48", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from google/t5-efficient-small-nl48: direct link, hf CLI and curl.
- Browser
- Download file 1.48 GB
-
https://huggingface.co/google/t5-efficient-small-nl48/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://google/t5-efficient-small-nl48/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/google/t5-efficient-small-nl48/resolve/main/pytorch_model.bin
1.48 GB
- Xet hash:
- 417b726c533a459d55777c855536bf307af383114801be1d90f5c8877b377c47
- Size of remote file:
- 1.48 GB
- SHA256:
- 12051ccfcf459de7557da0a15d75faf9bd11cb3faceed00bd49bb4e418ecfe94
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