Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-tiny-ff12000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-tiny-ff12000 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-tiny-ff12000") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-tiny-ff12000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-tiny-ff12000: direct link, hf CLI and curl.
- Browser
- Download file 247 MB
-
https://huggingface.co/google/t5-efficient-tiny-ff12000/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-tiny-ff12000/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-tiny-ff12000/resolve/main/flax_model.msgpack
247 MB
- Xet hash:
- e3953785f12606aba074819edb8fe788c264ae233c767e570f9b56d434a4fc01
- Size of remote file:
- 247 MB
- SHA256:
- 11b9446286add43f1a42e3167f37e9e4560803bafa2c1a5717a4dea0a54942d3
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