Instructions to use google/long-t5-local-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/long-t5-local-large with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/long-t5-local-large") model = AutoModelForSeq2SeqLM.from_pretrained("google/long-t5-local-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/long-t5-local-large: direct link, hf CLI and curl.
- Browser
- Download file 3 GB
-
https://huggingface.co/google/long-t5-local-large/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/long-t5-local-large/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/long-t5-local-large/resolve/main/flax_model.msgpack
3 GB
- Xet hash:
- 8fe8fdd295eb29f40b2a2c12c733ca5a342fe5a3999bbcdddd12a0e2f7b35f45
- Size of remote file:
- 3 GB
- SHA256:
- 7fcb80c51a31d99c56780a4af0bb289da89831ff233b85237e1621cf81a5257c
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