Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-tiny-nh1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-tiny-nh1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-tiny-nh1") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-tiny-nh1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from google/t5-efficient-tiny-nh1: direct link, hf CLI and curl.
- Browser
- Download file 52.9 MB
-
https://huggingface.co/google/t5-efficient-tiny-nh1/resolve/2b2cdc23e8f0fa26ba471bd78880cc52bd8104d1/pytorch_model.bin
- Command line
-
hf download hf://google/t5-efficient-tiny-nh1@2b2cdc23e8f0fa26ba471bd78880cc52bd8104d1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/google/t5-efficient-tiny-nh1/resolve/2b2cdc23e8f0fa26ba471bd78880cc52bd8104d1/pytorch_model.bin
52.9 MB
- Xet hash:
- f636cfad90d14cdfd6bb685007bdebca492fbb1a39f9b913ce2774d7ca99bca5
- Size of remote file:
- 52.9 MB
- SHA256:
- 0d95a874108e75890128c276f52eec02908aec2d1cd9e47f707bdc1bc30f7b55
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