Instructions to use google/t5-v1_1-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-v1_1-large with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-v1_1-large") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-v1_1-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-v1_1-large: direct link, hf CLI and curl.
- Browser
- Download file 3.13 GB
-
https://huggingface.co/google/t5-v1_1-large/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/t5-v1_1-large/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-v1_1-large/resolve/main/flax_model.msgpack
3.13 GB
- Xet hash:
- 0a20164ff04bbafc56d9741bcbf849af5d4775ea1b31479781b7fefc15f8e38c
- Size of remote file:
- 3.13 GB
- SHA256:
- 139f33b8a7887cd4ad38d812686f10e8c036226370b323585f4ecd89e992c7ff
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